Methods used in Life science to reuse data? How about annotation? Annotation derives information from a raw data set using different analyses, comparison, estimation, precision, and other mining…
Artificial Intelligence – It is the capacity of a computer, robot, or other programmed mechanical devices to perform operations and tasks analogous to learning and decision-making in humans, such as speech recognition or question answering. They are teaching human values to artificial intelligence. The branch of computer science involves the design of computers or other programmed mechanical devices having the capacity to imitate human intelligence and thought. Abbreviations: AI, A.I.
AI annotation in healthcare refers to the process of labeling and categorizing medical data to create a high-quality dataset for training artificial intelligence (AI) models in healthcare applications. Hypherdata can connect you to companies providing such services, or we can introduce companies offering these services to organisations requiring annotated data.
Some forms of annotation Hypherdata’s network covers and supports includes:
Medical Image Annotation
Electronic Health Record (EHR)
Diagnosis Annotation
Natural Language Processing (NLP) Annotation
Wearable and IoT Data Annotation
It’s crucial to ensure that the data used for AI annotation is carefully selected, and proper privacy and security measures are in place to protect patient information.
It is the practice of obtaining help in devising cutting-edge algorithms and machine learning tools so that organizations may create AI-driven solutions and products. In a nutshell, artificial intelligence consulting uses artificial intelligence to improve company operations.
Artificial intelligence as a Service (AIaaS) is AI outsourcing offered by third-party providers. So is a term that describes a third party that provides advanced AI functionalities to companies upon a one-time payment or subscription fee. It’s a set of off-the-shelf Solutions that can help businesses experiment with AI, implement it, and grow it at a fraction of the expense of building a custom in-house AI.
Hypherdata brings together Anesthesiology departments and units for potential real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Augmented analytics in healthcare refers to the use of advanced artificial intelligence (AI) and machine learning (ML) techniques to assist and enhance data analytics processes in the healthcare industry. It involves using AI algorithms to automate data preparation, analysis, and insight generation, empowering healthcare professionals with actionable insights and improving decision-making. Augmented analytics helps uncover hidden patterns, trends, and correlations in vast amounts of healthcare data, leading to better clinical outcomes, more efficient operations, and improved patient care.
Bias detection and prevention as a service in healthcare refers to a specialized offering that utilizes artificial intelligence (AI) to identify and mitigate bias in healthcare data and AI models.
This service involves the following components:
Bias Detection: AI algorithms analyze healthcare data and AI models to identify potential biases that may lead to inaccurate or unfair diagnosis or treatment of certain patient groups.
Bias Mitigation: The service employs various techniques, such as re-weighting data, applying fairness constraints, or adjusting model parameters to reduce or eliminate the bias.
Continuous Monitoring: Bias detection and prevention as a service provide ongoing monitoring and evaluation to ensure that the AI models remain fair and unbiased over time, as data and real-world dynamics change.
Hypherdata works with companies requiring and offering such services via its AI platform.
Biobanking is the process by which bodily fluid or tissue samples are collected, annotated, stored, and redistributed for research to improve understanding of health and diseases.
Biomarkers in healthcare are measurable indicators used to assess biological processes or disease states. The data collected are typically used to explain, influence, and/or predict health-related outcomes. Hypherdata works with data providers, researchers and AI solutions fuelling research and improved predictive, management and diagnostic outcomes.
Hypherdata brings together Cardiology departments and units for potential real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Claims data in healthcare refers to the records submitted by healthcare providers to insurance companies or payers for reimbursement. An AI solution company working with us can benefit from claims data by analyzing patterns, costs, and outcomes to improve healthcare decision-making, optimize treatment, and identify trends for research.
Hypherdata brings together Chemical chemistry specialists offering real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Clinical data refers to information collected during patient care, medical research, or clinical trials, providing insights into a patient’s health status, medical history, symptoms, diagnoses, treatments, and outcomes. This data includes various types, such as electronic health records (EHRs), laboratory test results, medical imaging reports, vital signs measurements, and information from clinical studies. Clinical data plays a fundamental role in healthcare decision-making, evidence-based medicine, and advancing medical knowledge and treatments.
Hypherdata works with relevant organizations within healthcare to make available such data, anonymized and compliant, for building or accelerating AI solutions and research in healthcare.
Clinical Trials Data accessible via Hypherdata’s network include
– Electronic health records (EHRs/EMRs)
– Genomic & genetic testing data
– Multi-omics data
– Imaging data
– Laboratory reports (e.g. pathology)
– Medical recordings
– Biomarker
– Patient registries
– Adverse Event Reports
– Case report forms (eCRF)
All data available is de-identified and anonymized, with additional annotation support where required through key partners.
This refers to the collection of raw data from both internal and external sources. The first phase of data collection involves identifying what data to collect and then establishing a process to do so (i.e., conducting a survey or retrieving automated IoT data). In general, new data assets remain difficult to source and access. More than 85% is not available to external parties.
Life science combines various pieces of data (medical research information, lab data, health records, etc.) Data often comes from multiple, separated systems. The intent is to create a unified, interconnective, and shareable source of truth.
Data analysis in healthcare involves the examination and interpretation of large volumes of healthcare data to gain valuable insights and inform decision-making. This process includes cleaning, transforming, and modeling the data to identify patterns, trends, correlations, and anomalies that can improve patient care, operational efficiency, and medical research.
Hypherdata works with companies who either provide or require such services.
Annotation in healthcare refers to the process of labeling and categorizing medical data to create a high-quality dataset. Hypherdata can connect you to companies providing such services, or we can introduce companies offering these services to organisations requiring annotated data towards AI solutions in healthcare.
Some forms of annotation Hypherdata’s network covers and supports includes:
Medical Image Annotation
Electronic Health Record (EHR)
Diagnosis Annotation
Natural Language Processing (NLP) Annotation
Wearable and IoT Data Annotation
It’s crucial to ensure that the data used for AI annotation is carefully selected, and proper privacy and security measures are in place to protect patient information.
Anonymization in healthcare refers to the process of removing or altering identifying information from patient data to protect individual privacy while retaining its usefulness for research, analysis, or other purposes. Hypherdata’s network comprises companies requiring and offering such services.
Data classification involves categorizing and organizing healthcare data based on its sensitivity and relevance to specific AI use cases.
Hypherdata works with companies with expertise in identifying and classifying data types such as medical images, electronic health records, genomic data, and clinical notes; in annotating said data (search AI / Data Annotation), and in ensuring its de-identification, anonymization, security and compliance.
Certain companies can assist healthcare AI companies by providing data cleaning services, ensuring data quality, and removing inconsistencies, errors, and redundancies from healthcare datasets.
Data curation in healthcare involves the selection, organization, and maintenance of valuable healthcare data to ensure its accuracy, relevance, and usability. Data quality benchmarks are based on data quality characteristics such as accuracy, completeness, consistency, validity, uniqueness, and timeliness.
Hypherdata’s network covers companies specializing in healthcare data curation, to transform data into measurable value for companies and research requiring these to build and enhance AI solutions.
Data enrichment in healthcare refers to the process of enhancing and expanding healthcare data by adding additional relevant information from external sources. This can involve validating and correcting existing data, appending new data attributes, and improving data quality to make it more valuable and insightful for analysis and decision-making.
Hypherdata’s network includes
– Healthcare Providers requiring or driving data enrichment via patient information validation, medical records updation, and multi-department data integration
– Specialized data analytics companies who can provide data enrichment services to healthcare organizations
– Third-party Data Providers providing socio-economic data, population demographics, or environmental factors, which can be integrated with existing healthcare data to enrich it.
– Government Agencies contributing to or requiring enriched data
– mHealth and eHealth applications
Hypherdata’s network encompasses companies working in both the data interoperability and data security space for both data providers and AI solutions looking to accelerate solutions and outcomes.
Data infrastructure in healthcare refers to the underlying technology and architecture that supports the collection, storage, processing, and management of healthcare data. It includes databases, data warehouses, data lakes, cloud storage, networking, and other IT components that facilitate the secure and efficient handling of healthcare information.
Hypherdata works with large infrastructure companies that have built our own solution, and continue to lend support to data providers and AI solutions building or enhancing their offering.
Data integration in healthcare refers to the process of combining and harmonizing data from various sources and systems into a unified and coherent view. It involves connecting and consolidating disparate data to facilitate seamless data sharing, analysis, and decision-making. Hypherdata works with data integration and interoperability solution providers to facilitate data movement from providers to AI solutions and researchers building or enhancing their offering.
Data labeling is the process of annotating or tagging data with specific labels or categories to provide meaningful context and make the data usable for machine learning and AI applications. Data labeling is essential for supervised learning algorithms, where labeled data is used to train AI models to recognize patterns and make accurate predictions.
Hypherdata collaborates with data labeling companies to ensure accurate and relevant annotations, enabling seamless integration of labeled data into AI solutions and supporting researchers and developers in building or enhancing their offerings.
Data modeling is the process of creating a conceptual representation of data structures, relationships, and rules to design databases and information systems. It involves defining data entities, attributes, and their interactions to ensure data accuracy, consistency, and efficient data retrieval.
Hypherdata collaborates with companies seeking support to enhance their AI or algorithm models. They provide services that enable seamless integration of data models, optimizing data retrieval and improving the overall performance of AI solutions.
Data pseudonymization, anonymization, and de-identification are related privacy techniques used to protect sensitive information while allowing data to be used for research and analysis.
Pseudonymization involves replacing or encrypting identifying information in a dataset with pseudonyms or codes. The data can still be linked back to the original identity using a separate key. Pseudonymization provides a reversible way to protect privacy and allows limited re-identification by authorized parties.
Hypherdata’s network comprises companies requiring and offering such services.
It makes data available by an organization that initially created or collected the data. Data sharing can be unilateral or multilateral. It may take the form of an exchange of data or the creation of a centralized repository or data pool.
Data pseudonymization, anonymization, and de-identification are related privacy techniques used to protect sensitive information while allowing data to be used for research and analysis.
De-identification is a broader term that includes both pseudonymization and anonymization. It refers to the process of removing or obfuscating any direct or indirect identifiers from data to protect individual privacy. De-identified data cannot be linked back to individuals without additional information thereby allowing data to confirm to privacy norms.
Hypherdata’s network comprises companies requiring and offering such services.
Hypherdata brings together Dentists both independent and within large clinic or hospital setups for potential real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Hypherdata brings together Dermatology departments and clinicians for potential real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Objective, quantifiable physiological and behavioral data collected and measured using digital devices such as portables, wearables, implantables, digestible, or static hospital equipment – e.g., lung breathing machines etc. The data collected are typically used to explain, influence, and/or predict health-related outcomes.
Electronic Health Records or Electronic Medical Records are digital versions of a patient’s medical record that contains their health information, medical history, treatment plans, test results, medications, allergies, and other relevant medical data. For certain medical areas, analysed data from these records particularly benefits studies and AI algorithms for healthcare software solutions.
Hypherdata works with relevant organizations within healthcare to make available such data, anonymized and compliant, for building or accelerating AI solutions and research in healthcare.
Hypherdata brings together Emergency Medicine departments and specialists with real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Hypherdata brings together Endocrinology experts both independent and within large clinic or hospital setups for potential real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Hypherdata works with companies specializing in ethical AI, offering a range of services to ensure that AI technologies and applications are developed, deployed, and used responsibly and in compliance with ethical principles.
These services could include Ethical AI Consulting for solution deployment, AI Ethics Training, Ethical AI Framework Development, AI Impact Assessments, Bias Detection and Mitigation, AI Governance, AI Ethical Audits, AI Policy and Compliance, Ethical AI Certification and more.
Hypherdata works with companies specializing in FAIR (Findable, Accessible, Interoperable, and Reusable) data who offer a range of services to help organizations improve the management, sharing, and usability of their data. Some of the services they may provide include Data Standardization, Data Integration and Interoperability, Data Cataloging and Indexing, Data Repository Development, Data Linking and Aggregation, Data Quality Assessment, Data Sharing, Privacy and Collaboration, Data Citation and Attribution, along with FAIR Data Training.
Hypherdata works with AI and platform solutions and data providers towards accessing de-identified Family Health and Treatment History Data in healthcare including but not limited to medical conditions and treatment outcomes via self-reported information and EHR / EMR. AI solutions can benefit from such data to personalize care, identify genetic predispositions, personalize treatment plans, and predict disease risks for patients.
Hypherdata brings together General Physicians and Family medicine specialists both independent and within large clinic or hospital setups for potential real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Hypherdata works with providers of Wearable data such as fitness trackers and smartwatches and connects them with AI companies building or enhancing solutions and healthcare breakthroughs using these datasets.
Hypherdata brings together Gastroenterology experts both independent and within large clinic or hospital setups for potential real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
The General Data Protection Regulation (GDPR) outlines specific rules that protect user data and create transparency. While the GDPR is strict, it permits companies to collect anonymized data without consent, use it for any purpose, and store it indefinitely—as long as companies remove all identifiers from the data.
Hypherdata works with companies specializing in providing GDPR compliance services to healthcare offers solutions like GDPR assessments, data mapping, privacy policy updates, data subject rights management, and DPO support. They help organizations meet GDPR requirements and protect patient data while building trust with stakeholders.
GDPR -outlines specific rules that protect user data and create transparency. While the GDPR is strict, it permits companies to collect anonymized data without consent, use it for any purpose, and store it indefinitely—as long as companies remove all identifiers from the data.
Genomic testing focuses on sequencing an individual’s entire genome, while genetic testing may target specific genes or regions of the genome to identify variations or mutations. Genomic and genetic testing data can be used to build healthcare AI solutions in several ways:
– Personalized Medicine
– Disease Risk Prediction
– Cancer Genomics
– Rare Disease Diagnosis
– How an individual will respond to certain drugs, optimizing drug selection and dosages
– targeted gene-editing interventions.
For optimal genomic and gene testing data, Hypherdata works with companies to organise the following steps:
– Data Matchmaking with the right providers
– Data Preprocessing
– Feature Engineering for AI model input
– Support with AI Model Development
– Solution and Service Deployment
Hypherdata brings together Geriatrics experts both independent and within large clinic or hospital setups for potential real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Hypherdata works with companies offering health data visualization services for valuable support in building or enhancing their algorithms and models. Some of the services that can benefit AI solutions in this context include Data Preprocessing Visualization, Feature Selection Visualization, Model Performance Visualization to assess accuracy, sensitivity, specificity, etc., aiding in model evaluation and improvement, Explainability Visualization ensuring transparency and trustworthiness, Model Training Progress Visualization, Data Imbalance Visualization and Error Analysis Visualization.
Hypherdata brings together Hematology experts both independent and within large clinic or hospital setups for potential real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Hypherdata works with companies specializing in providing HIPAA compliance services to healthcare. The services and solutions include readiness assessment, policy development, training, risk analysis, breach response plans, BAAs negotiation, security controls implementation, audits, documentation management, and technical safeguards implementation. They ensure adherence to HIPAA regulations, safeguard protected health information, and mitigate security risks.
Imaging data refers to a type of medical data that includes various visual representations of a patient’s internal body structures or organs and can range from X-Rays to Ultrasounds, CT Scans, MRIs, PET and SPECT scans
Hypherdata works with relevant organizations within healthcare to make available such data, anonymized and both PACS and DICOM compliant for ease of use, for building or accelerating AI solutions and research in healthcare.
Hypherdata brings together Infectious disease experts both independent and within large clinic or hospital setups for potential real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Hypherdata brings together Internal medicine experts both independent and within large clinic or hospital setups for potential real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Hypherdata works with providers of IoT data such as connected medical devices and sensors and connects them with AI companies building or enhancing solutions and healthcare breakthroughs using these datasets.
Data within lab reports that can contribute to helping companies in healthcare AI include various types of structured information obtained from laboratory tests. Some key data points include available anonymised and annotated, include:
* Test Results with Reference Ranges, Units of Measurement & Test Names and Codes
* Timestamps for when the lab tests were conducted, enabling temporal analysis and tracking changes over time
* Patient Demographics
* Ordering Physician Information to determine the context and reason for the tests
* Test Methodologies
* Diagnosis and Clinical Notes
Hypherdata works with relevant organizations within healthcare to make available such data in a structured and confidential manner for companies and researchers building or accelerating AI solutions and research in healthcare.
Medical Claims data in healthcare refers to the records submitted by healthcare providers to insurance companies or payers for reimbursement. An AI solution company working with us can benefit from claims data by analyzing patterns, costs, and outcomes to improve healthcare decision-making, optimize treatment, and identify trends for research.
Medical (clinical) data refers to health-related information that is associated with regular patient care or as part of a clinical trial program. This data covers several modalities and extends across all medical areas.
At Hypherdata, we are accelerating AI-driven healthcare breakthroughs by building a global network of data, services and knowledge providers with companies building AI solutions and services, or research in this area.
Hypherdata works with medical device manufacturers and device data aggregators to connect their cleaned and annotated data with AI companies building or enhancing solutions and healthcare breakthroughs using these datasets.
Medical recordings refer to audio or video recordings made for healthcare purposes, such as documenting patient interactions, medical procedures, surgeries, and clinical examinations.
Hypherdata works with relevant organizations within healthcare to make available such data, de-identified, anonymized and aggregated, for companies and researchers building or accelerating AI solutions and research in healthcare.
Hypherdata works with AI solutions, pharmaceutical companies and data providers towards accessing de-identified Medication-related Data with the ultimate goal of optimizing drug therapies, reducing medication errors, improving patient adherence and outcomes through personalized treatment recommendations.
Hypherdata brings together Microbiology experts both independent and within large clinic or hospital setups for potential real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Hypherdata works with providers of Mobile Health (mHealth) data, collected through mobile devices or wearables, such as smartphones, fitness trackers, and smartwatches and connects them with AI companies building or enhancing solutions and healthcare breakthroughs using these datasets.
Hypherdata works with providers of Mobile Health (mHealth) data, collected through mobile devices or wearables, such as smartphones, fitness trackers, and smartwatches and connects them with AI companies building or enhancing solutions and healthcare breakthroughs using these datasets.
Common techniques used in molecular profiling include DNA sequencing, RNA sequencing, protein analysis, metabolomics, and other high-throughput molecular assays. The information obtained from molecular profiling can lead to more precise and effective healthcare interventions, advancing the field of precision medicine.
Hypherdata works with relevant organizations within healthcare to make available such data, de-identified, anonymized and aggregated, for companies and researchers building or accelerating AI solutions and research in healthcare.
Multi-omics data refers to the integration and analysis of multiple types of biological data from different “omics” technologies. “Omics” refers to various branches of biology that study specific molecules or components within an organism, such as genomics (study of genes and their functions), transcriptomics (study of RNA expression), proteomics (study of proteins), metabolomics (study of metabolites), and epigenomics (study of changes in gene expression caused by modifications to DNA).
Hypherdata works with relevant organizations within healthcare to make available such data, and collaborates with AI solutions building algorithms to identify disease biomarkers, disease pathways, accelerate or enhance drug discovery, and precision medicine.
Hypherdata brings together Nephrology experts both independent and within large clinic or hospital setups for potential real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Hypherdata brings together Obstetrics and gynecology experts both independent and within large clinic or hospital setups for potential real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Hypherdata brings together Oncologists both independent and within large clinic or hospital setups for potential real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Hypherdata brings together Ophthalmologists both independent and within large clinic or hospital setups for potential real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Hypherdata brings together Orthopedics both independent and within large clinic or hospital setups for potential real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Hypherdata brings together Otolaryngology (ear, nose, and throat) experts, better known as ENTs, both independent and within large clinic or hospital setups for potential real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Imaging data refers to a type of medical data that includes various visual representations of a patient’s internal body structures or organs and can range from X-Rays to Ultrasounds, CT Scans, MRIs, PET and SPECT scans.
Hypherdata works with relevant organizations within healthcare to make available such data, anonymized and both PACS and DICOM compliant for ease of use, for building or accelerating AI solutions and research in healthcare.
Hypherdata brings together Pathology departments and independent Path Labs offering real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Hypherdata works with AI and platform solutions and data providers towards accessing de-identified Patient-reported data in healthcare including but not limited to health status, symptoms, experiences, and treatment outcomes. AI solutions can benefit from such data to personalize care, monitor patient progress, and improve treatment efficacy.
Hypherdata works with AI and platform solutions and data providers towards accessing de-identified Patient Reported Outcomes (PROs) in healthcare including but not limited to self-reported information from patients about their health-related quality of life, symptoms, functional status, and treatment satisfaction. AI solutions can benefit from such data to personalize care, monitor patient progress, and improve treatment efficacy.
Hypherdata brings together Pediatrics both independent and within large clinic or hospital setups for potential real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Hypherdata brings together Physical medicine and rehabilitation specialists, clinicians and hospitals offering real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Hypherdata brings together Plastic surgeons, clinicians and hospitals offering real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Prescription drug claims data in healthcare includes records of medications prescribed and filled by patients. Aa a company working in this area, you can benefit from Hypherdata’s network by intelligent prescriptions and subscription management, analysis of drug utilization patterns, medication adherence, and other AI solutions in patient care and drug safety.
Hypherdata brings together Psychiatrists, both independent clinicians and in hospitals offering real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Hypherdata brings together Pulmonologists and large hospital departments offering real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Hypherdata brings together Radiologists and large hospital departments offering real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Real-world data, as defined by U.S. FDA, are data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources. Examples of RWD include data derived from electronic health records, medical claims data, data from product or disease registries, and data gathered from other sources (such as digital health technologies) that can inform on health status.
Hypherdata works with hospitals, clinicians and organizations who provide such data for building or accelerating AI solutions and research in healthcare.
Hypherdata brings together Rheumatology experts both independent and within large clinic or hospital setups for potential real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation. Rheumatology research particularly benefits from studies using EHR data as Rheumatic conditions are generally uncommon and To enrol sufficient numbers of patients for population-based studies requires years to decades.
Hypherdata works with data providers, AI solutions and related services to ensure all data and service exchanges take place in a secure manner, adhering to the highest standards of security, privacy and prevailing compliance. Additionally, we are a closed marketplace ensuring confidentiality of requirements, data availability and deals.
Search for Data Anonymisation, De-identification, Aggregation and Integration, Pseudonymization, HIPAA and GDPR Compliance to know more about ways to secure data for research and algorithms purposes.
Hypherdata brings together Urologists and large hospital departments offering real world data and AI solutions working within this field who with to to build and / or strengthen their offering. The information and services can accelerate AI breakthroughs and drive both research and innovation.
Hypherdata works with providers of Wearable data such as fitness trackers and smartwatches and connects them with AI companies building or enhancing solutions and healthcare breakthroughs using these datasets.