Best AI tools for< Analyze Patient Data >

Glass is an AI-powered clinical decision support platform that empowers clinicians by providing differential diagnoses and drafting clinical plans based on patient summaries. The platform combines a large language model with evidence-based clinical guidelines to assist clinicians in making informed decisions. Glass Health aims to optimize the practice of medicine, improve patient care, increase diagnostic accuracy, implement evidence-based treatment, enhance medical education, eliminate burnout, accelerate health equity, and improve patient outcomes globally.

Tempus is an AI-enabled precision medicine company that brings the power of data and artificial intelligence to healthcare. With the power of AI, Tempus accelerates the discovery of novel targets, predicts the effectiveness of treatments, identifies potentially life-saving clinical trials, and diagnoses multiple diseases earlier. Tempus' innovative technology includes ONE, an AI-enabled clinical assistant; NEXT, which identifies and closes gaps in care; LENS, which finds, accesses, and analyzes multimodal real-world data; and ALGOS, algorithmic models connected to Tempus' assays to provide additional insight.

GenHealth.ai is a cutting-edge AI application focused on generative healthcare AI. The platform offers innovative solutions for healthcare organizations by leveraging a Large Medical Model (LMM) trained on vast amounts of patient data. GenHealth.ai provides automated prior authorization, healthcare analytics, and predictive modeling to help healthcare leaders make informed decisions and optimize patient care. The application stands out for its ability to simulate patient futures, predict healthcare costs, and integrate with healthcare standards like FHIR, HL7, and X12.

Owkin is a full-stack AI biotech company that integrates the best of human and artificial intelligence to deliver better drugs and diagnostics at scale. By understanding complex biology through AI, Owkin identifies new treatments, de-risks and accelerates clinical trials, and builds diagnostic tools to reduce time to impact for patients.

Oncora Medical is a healthcare technology company that provides software and data solutions to oncologists and cancer centers. Their products are designed to improve patient care, reduce clinician burnout, and accelerate clinical discoveries. Oncora's flagship product, Oncora Patient Care, is a modern, intelligent user interface for oncologists that simplifies workflow, reduces documentation burden, and optimizes treatment decision making. Oncora Analytics is an adaptive visual and backend software platform for regulatory-grade real world data analytics. Oncora Registry is a platform to capture and report quality data, treatment data, and outcomes data in the oncology space.

Komodo Health is a healthcare technology company that provides software applications to enable users to deliver exceptional value to their customers, colleagues, and patients. The company's Healthcare Map is the industry's most precise view of the U.S. healthcare system, and it combines the world's most comprehensive view of patient-encounters with innovative algorithms and decades of clinical expertise. Komodo Health's software applications are used by life sciences companies, payers, providers, and consultancies to improve the certainty of pre-launch plans, calculate Rx-based ROI for digital marketing, find patients with complicated or rare conditions, and more.

AiCure provides a patient-centric eClinical trial management platform that enhances drug development through improved medication adherence rates, more powerful analysis and prediction of treatment response using digital biomarkers, and reduced clinical tech burden. AiCure's solutions support traditional, decentralized, or hybrid trials and offer flexibility to meet the needs of various research designs.

IXICO is a precision analytics company specializing in intelligent insights in neuroscience. They offer a range of services for drug development analytics, imaging operations, and post-marketing consultancy. With a focus on technology and innovation, IXICO provides expertise in imaging biomarkers, radiological reads, volumetric MRI, PET & SPECT, and advanced MRI. Their TrialTracker platform and Assessa tool utilize innovation and AI for disease modeling and analysis. IXICO supports biopharmaceutical companies in CNS clinical research with cutting-edge neuroimaging techniques and AI technology.

BetterMedicine is an AI software designed for cancer diagnostics and detection. It offers AI-powered solutions to enhance patient outcomes and drive efficiency in radiology workflows. The software is expertly designed by medical professionals and AI specialists, providing trusted and clinically validated solutions. BetterMedicine aims to address inefficiencies in radiology by integrating AI-powered software for detecting lesions on CT scans seamlessly into the workflow, thereby improving efficiency and reducing the risk of oversight. The application focuses on improving patient outcomes, reducing errors, and enhancing the wellbeing of radiology professionals.

Binah.ai is an AI-powered Health Data Platform that offers a software solution for video-based vital signs monitoring. The platform enables users to measure various health and wellness indicators using a smartphone, tablet, or laptop. It provides support for continuous monitoring through a raw PPG signal from external sensors and offers a range of features such as blood pressure monitoring, heart rate variability, oxygen saturation, and more. Binah.ai aims to make health data more accessible for better care at lower costs by leveraging AI and deep learning algorithms.

Apixio is a healthcare AI company that provides solutions for health plans, providers, and ACOs. Their AI-powered platform helps organizations improve administrative, clinical, and financial outcomes. Apixio's solutions include risk adjustment, payment integrity, health data management, and AI-as-a-service.

Tempus is an AI-enabled precision medicine company that brings the power of data and artificial intelligence to healthcare. With the power of AI, Tempus accelerates the discovery of novel targets, predicts the effectiveness of treatments, identifies potentially life-saving clinical trials, and diagnoses multiple diseases earlier. Tempus's innovative technology includes ONE, an AI-enabled clinical assistant; NEXT, a tool to identify and close gaps in care; LENS, a platform to find, access, and analyze multimodal real-world data; and ALGOS, algorithmic models connected to Tempus's assays to provide additional insight.

CloudMedx is a healthcare data platform that provides aggregation, automation, and AI solutions. It simplifies decision making for patients, providers, and payers with a single powerful platform. Clinical, operations, and financial results are coordinated and delivered like never before.

Biofourmis is a healthcare technology company that provides a connected technology platform for care delivery and drug development. The platform enables healthcare systems and pharmaceutical companies to deliver care and conduct clinical trials remotely, and to collect and analyze data to improve patient outcomes. Biofourmis's solutions have been shown to improve clinical, operational, and economic outcomes, such as reducing 30-day readmissions by 70%, detecting deterioration 21 hours sooner, and reducing cost of care by up to 38%.

Health Imaging is an AI-powered platform that focuses on providing cutting-edge solutions in medical imaging and healthcare management. The platform offers a wide range of features and tools that leverage artificial intelligence to enhance diagnostic accuracy, streamline workflows, and improve patient care. From advanced imaging technologies to AI-based training solutions, Health Imaging is at the forefront of innovation in the healthcare industry.

The website is an AI tool focused on providing news, insights, and updates on the application of artificial intelligence in the healthcare industry. It covers a wide range of topics such as digital transformation, care delivery, and AI regulations. The platform aims to educate and inform healthcare professionals, industry watchers, and stakeholders about the latest trends, challenges, and opportunities in leveraging AI for improving patient care and healthcare operations.

MeDA School is an educational platform dedicated to promoting and nurturing talents in the field of Medical Artificial Intelligence (AI). The platform aims to establish a solid foundation for intelligent and precision medical talent pools in Taiwan and globally. MeDA School facilitates interaction and communication among members of the intelligent medical ecosystem, fostering deep understanding and trust in the operation and tasks of medical AI. The platform offers a blend of virtual and physical courses, inviting domain experts to share cutting-edge knowledge and integrating interdisciplinary knowledge to be practically applied in various fields.

Iterative Health is a company that is dedicated to providing world-class GI care and treatment to patients around the world. They are on a mission to bring world-class care and treatment to patients around the world. Advances in machine learning and artificial intelligence are helping them create a complete GI ecosystem with the power to turn this vision into reality.

Beacon Biosignals provides an EEG neurobiomarker platform that is designed to accelerate clinical trials and enable new treatments for patients with neurological and psychiatric diseases. Their platform is powered by machine learning and a world-class clinico-EEG database, which allows them to analyze existing EEG data for insights into mechanisms, PK/PD, and patient stratification. This information can be used to guide further development efforts, optimize clinical trials, and enhance understanding of treatment efficacy.

ICD AI is an advanced artificial intelligence tool designed to assist healthcare professionals in accurately assigning diagnostic codes to patient records. The tool utilizes machine learning algorithms to analyze medical data and suggest appropriate ICD codes, streamlining the coding process and reducing errors. With its user-friendly interface and robust features, ICD AI is revolutionizing medical coding practices and improving efficiency in healthcare facilities.

Open Life Science AI: Medical Reasoning Tasks is a collaborative hub for developing cutting-edge reasoning tasks for Large Language Models (LLMs) in the medical, healthcare, and clinical domains. The repository aims to advance AI capabilities in healthcare by fostering accurate diagnoses, personalized treatments, and improved patient outcomes. It offers a diverse range of medical reasoning challenges such as Diagnostic Reasoning, Treatment Planning, Medical Image Analysis, Clinical Data Interpretation, Patient History Analysis, Ethical Decision Making, Medical Literature Comprehension, and Drug Interaction Assessment. Contributors can join the community of healthcare professionals, AI researchers, and enthusiasts to contribute to the repository by creating new tasks or improvements following the provided guidelines. The repository also provides resources including a task list, evaluation metrics, medical AI papers, and healthcare datasets for training and evaluation.

LLMonFHIR is an iOS application that utilizes large language models (LLMs) to interpret and provide context around patient data in the Fast Healthcare Interoperability Resources (FHIR) format. It connects to the OpenAI GPT API to analyze FHIR resources, supports multiple languages, and allows users to interact with their health data stored in the Apple Health app. The app aims to simplify complex health records, provide insights, and facilitate deeper understanding through a conversational interface. However, it is an experimental app for informational purposes only and should not be used as a substitute for professional medical advice. Users are advised to verify information provided by AI models and consult healthcare professionals for personalized advice.

Seismometer is a suite of tools designed to evaluate AI model performance in healthcare settings. It helps healthcare organizations assess the accuracy of AI models and ensure equitable care for diverse patient populations. The tool allows users to validate model performance using standardized evaluation criteria based on local data and workflows. It includes templates for analyzing statistical performance, fairness across different cohorts, and the impact of interventions on outcomes. Seismometer is continuously evolving to incorporate new validation and analysis techniques.

Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment interfaces and libraries for understanding AI systems. It empowers developers and stakeholders to develop and monitor AI responsibly, enabling better data-driven actions. The toolbox includes visualization widgets for model assessment, error analysis, interpretability, fairness assessment, and mitigations library. It also offers a JupyterLab extension for managing machine learning experiments and a library for measuring gender bias in NLP datasets.

Awesome-Segment-Anything is a powerful tool for segmenting and extracting information from various types of data. It provides a user-friendly interface to easily define segmentation rules and apply them to text, images, and other data formats. The tool supports both supervised and unsupervised segmentation methods, allowing users to customize the segmentation process based on their specific needs. With its versatile functionality and intuitive design, Awesome-Segment-Anything is ideal for data analysts, researchers, content creators, and anyone looking to efficiently extract valuable insights from complex datasets.

llm_benchmarks is a collection of benchmarks and datasets for evaluating Large Language Models (LLMs). It includes various tasks and datasets to assess LLMs' knowledge, reasoning, language understanding, and conversational abilities. The repository aims to provide comprehensive evaluation resources for LLMs across different domains and applications, such as education, healthcare, content moderation, coding, and conversational AI. Researchers and developers can leverage these benchmarks to test and improve the performance of LLMs in various real-world scenarios.

Phi-3-MLX is a versatile AI framework that leverages both the Phi-3-Vision multimodal model and the Phi-3-Mini-128K language model optimized for Apple Silicon using the MLX framework. It provides an easy-to-use interface for a wide range of AI tasks, from advanced text generation to visual question answering and code execution. The project features support for batched generation, flexible agent system, custom toolchains, model quantization, LoRA fine-tuning capabilities, and API integration for extended functionality.

This repository contains a comprehensive collection of 63 must-know Large Language Models (LLMs) interview questions. It covers topics such as the architecture of LLMs, transformer models, attention mechanisms, training processes, encoder-decoder frameworks, differences between LLMs and traditional statistical language models, handling context and long-term dependencies, transformers for parallelization, applications of LLMs, sentiment analysis, language translation, conversation AI, chatbots, and more. The readme provides detailed explanations, code examples, and insights into utilizing LLMs for various tasks.

Swarms provides simple, reliable, and agile tools to create your own Swarm tailored to your specific needs. Currently, Swarms is being used in production by RBC, John Deere, and many AI startups.

Greenplum Database (GPDB) is an advanced, fully featured, open source data warehouse, based on PostgreSQL. It provides powerful and rapid analytics on petabyte scale data volumes. Uniquely geared toward big data analytics, Greenplum Database is powered by the world’s most advanced cost-based query optimizer delivering high analytical query performance on large data volumes.

The repository 'LLM-for-Healthcare' provides a comprehensive survey of large language models (LLMs) for healthcare, covering data, technology, applications, and accountability and ethics. It includes information on various LLM models, training data, evaluation methods, and computation costs. The repository also discusses tasks such as NER, text classification, question answering, dialogue systems, and generation of medical reports from images in the healthcare domain.

TrustLLM is a comprehensive study of trustworthiness in LLMs, including principles for different dimensions of trustworthiness, established benchmark, evaluation, and analysis of trustworthiness for mainstream LLMs, and discussion of open challenges and future directions. Specifically, we first propose a set of principles for trustworthy LLMs that span eight different dimensions. Based on these principles, we further establish a benchmark across six dimensions including truthfulness, safety, fairness, robustness, privacy, and machine ethics. We then present a study evaluating 16 mainstream LLMs in TrustLLM, consisting of over 30 datasets. The document explains how to use the trustllm python package to help you assess the performance of your LLM in trustworthiness more quickly. For more details about TrustLLM, please refer to project website.

searchGPT is an open-source project that aims to build a search engine based on Large Language Model (LLM) technology to provide natural language answers. It supports web search with real-time results, file content search, and semantic search from sources like the Internet. The tool integrates LLM technologies such as OpenAI and GooseAI, and offers an easy-to-use frontend user interface. The project is designed to provide grounded answers by referencing real-time factual information, addressing the limitations of LLM's training data. Contributions, especially from frontend developers, are welcome under the MIT License.

This repository serves as a practical guide for Medical Large Language Models (Medical LLMs) and provides resources, surveys, and tools for building, fine-tuning, and utilizing LLMs in the medical domain. It covers a wide range of topics including pre-training, fine-tuning, downstream biomedical tasks, clinical applications, challenges, future directions, and more. The repository aims to provide insights into the opportunities and challenges of LLMs in medicine and serve as a practical resource for constructing effective medical LLMs.

Awesome-llm-role-playing-with-persona is a curated list of resources for large language models for role-playing with assigned personas. It includes papers and resources related to persona-based dialogue systems, personalized response generation, psychology of LLMs, biases in LLMs, and more. The repository aims to provide a comprehensive collection of research papers and tools for exploring role-playing abilities of large language models in various contexts.

The LLMEvaluation repository is a comprehensive compendium of evaluation methods for Large Language Models (LLMs) and LLM-based systems. It aims to assist academics and industry professionals in creating effective evaluation suites tailored to their specific needs by reviewing industry practices for assessing LLMs and their applications. The repository covers a wide range of evaluation techniques, benchmarks, and studies related to LLMs, including areas such as embeddings, question answering, multi-turn dialogues, reasoning, multi-lingual tasks, ethical AI, biases, safe AI, code generation, summarization, software performance, agent LLM architectures, long text generation, graph understanding, and various unclassified tasks. It also includes evaluations for LLM systems in conversational systems, copilots, search and recommendation engines, task utility, and verticals like healthcare, law, science, financial, and others. The repository provides a wealth of resources for evaluating and understanding the capabilities of LLMs in different domains.

Slideflow is a deep learning library for digital pathology, offering a user-friendly interface for model development. It is designed for medical researchers and AI enthusiasts, providing an accessible platform for developing state-of-the-art pathology models. Slideflow offers customizable training pipelines, robust slide processing and stain normalization toolkit, support for weakly-supervised or strongly-supervised labels, built-in foundation models, multiple-instance learning, self-supervised learning, generative adversarial networks, explainability tools, layer activation analysis tools, uncertainty quantification, interactive user interface for model deployment, and more. It supports both PyTorch and Tensorflow, with optional support for Libvips for slide reading. Slideflow can be installed via pip, Docker container, or from source, and includes non-commercial add-ons for additional tools and pretrained models. It allows users to create projects, extract tiles from slides, train models, and provides evaluation tools like heatmaps and mosaic maps.

Mojo is a new programming language that bridges the gap between research and production by combining Python syntax and ecosystem with systems programming and metaprogramming features. Mojo is still young, but it is designed to become a superset of Python over time.

Implementation of the general framework for AMIE, from the paper Towards Conversational Diagnostic AI, out of Google Deepmind. This repository provides a Pytorch implementation of the AMIE framework, aimed at enabling conversational diagnostic AI. It is a work in progress and welcomes collaboration from individuals with a background in deep learning and an interest in medical applications.

Expert in Orthopaedic Bioengineering

I assist in analyzing stocks with a detail-oriented, patient, data-driven approach, drawing from a wide range of expert authors.

This GPT will take a user's data and use it to construct a fake TV scene. Start by providing it with your character's Patient Profile, Diagnostic Findings, and Lab Data

Expert in healthcare data analysis, coding, and clinical trials.

A knowledgeable and patient teacher in logistics, offering insights and guidance.

Insights on AI in healthcare and wellness

구체화 수식 및 raw data 제안이 포함된 아이디어 특허 도움

Japanese patent data graph generator with user engagement

Assist users with matters related to patents

This GPT explains the US11769017B1 patent and how it relates to Google's SGE (Search Generative Experience).

Turbocharge your research and streamline your path to breakthrough findings. Leveraging the vast resources of PubChem, this GPT taps into a wealth of chemical data—from substances to proteins and patents—unleashing the full potential of your data for richer, more informed discoveries.

A Master Researcher with vast experience in science and technology analysis.

Expert in genomics, AI, and medical tech, explaining complex concepts simply.

Find recent research for your area of biological interest.

Direct, insightful EEG and neurofeedback analysis specialist.

Patient threat intelligence expert skilled in binary file analysis and YARA rules.

Su Médico personal. Su Cita Médica 24/7 Analizo Examenes Médicos y de Laboratorio!

Expert on marketing to foreign patients in Korea

Helps with valuation and evaluation of your patent