Best AI tools for< Clinical Informaticist >

DeepScribe is an AI medical scribe application that leverages advanced speech recognition technology to capture clinical conversations with extreme accuracy. It empowers clinicians and health systems with real-time AI insights, offers customization options to match provider workflows, and ensures trust and safety through features that promote AI transparency. DeepScribe is designed to save time, improve accuracy, drive adoption, and maximize revenue for doctors, hospitals, and health systems. The application is built for enterprise use, allowing users to unlock the power of AI and modernize their patient data strategy.

InformAI is a technology company dedicated to advancing healthcare through the development of AI-driven solutions. We focus on crafting high-quality, AI-driven enterprise software solutions that address specific clinical needs. We target critical medical fields including radiology, radiation oncology, and high acuity informatics. Our portfolio, featuring our flagship RadOncAI and our development pipeline products of SinusAI and TransplantAI, is designed to deliver impactful solutions that enhance healthcare quality, safety and efficiency.

JMIR AI is a new peer-reviewed journal focused on research and applications for the health artificial intelligence (AI) community. It includes contemporary developments as well as historical examples, with an emphasis on sound methodological evaluations of AI techniques and authoritative analyses. It is intended to be the main source of reliable information for health informatics professionals to learn about how AI techniques can be applied and evaluated.

Decode Health is an AI and analytics platform that accelerates precision healthcare by supporting healthcare teams in launching machine learning and advanced analytics projects. The platform collaborates with pharmaceutical companies to enhance patient selection, biomarker identification, diagnostics development, data asset creation, and analysis. Decode Health offers modules for biomarker discovery, patient recruitment, next-generation sequencing, data analysis, and clinical decision support. The platform aims to provide fast, accurate, and actionable insights for acute and chronic disease management. Decode Health's custom-built modules are designed to work together to solve complex data problems efficiently.

Healthcare IT News is an AI-powered platform that provides the latest news and updates in the healthcare IT industry. The platform covers a wide range of topics including video analytics, artificial intelligence, cloud computing, EHR, government & policy, interoperability, patient engagement, population health, precision medicine, privacy & security, and telehealth. It offers insights, articles, and special projects related to AI, ML intelligence, cybersecurity, and more. Healthcare IT News aims to keep healthcare professionals informed about the latest trends and developments in the field.

Cosign AI is an AI application that optimizes clinical practices by automating clinical documentation through an ambient scribe. The tool transforms conversations and dictations into clinical notes using large language models and customizable templates. It prioritizes HIPAA compliance and data security, ensuring a secure infrastructure for storing and processing protected health information. Clinicians can save time, reduce burnout, and improve note quality with this innovative solution.

Abridge is an enterprise-grade AI platform for clinical conversations, integrated directly inside Epic. It transforms patient-clinician conversations into structured clinical notes in real-time, powered by advanced generative AI technology. Abridge saves hours of time-consuming documentation per clinician every month, provides clinically accurate summaries and medical terms across specialties, recognizes and takes accurate notes across a wide range of languages, and creates complete, highly accurate, structured clinical note drafts. The platform aims to return time to healthcare teams, clarity to patients, and efficiencies to healthcare systems, ultimately reducing burnout among clinicians.

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.

Mendel AI is an advanced clinical AI tool that deciphers clinical data with clinician-like logic. It offers a fully integrated suite of clinical-specific data processing products, combining OCR, de-identification, and clinical reasoning to interpret medical records. Users can ask questions in plain English and receive accurate answers from health records in seconds. Mendel's technology goes beyond traditional AI by understanding patient-level data and ensuring consistency and explainability of results in healthcare.

Health AI Partnership (HAIP) is an AI tool designed to empower healthcare professionals to effectively, safely, and equitably use AI through community-informed up-to-date standards. The platform offers resources, publications, events, and a practice network to advance the use of AI in healthcare and support professionals in implementing AI solutions.

Medlabreport.com is an AI-powered platform that helps users understand their medical exam results easily. By uploading a file, users receive a comprehensive report within 5 minutes, focusing on personalized insights based on symptoms, age, and other factors. The platform's advanced AI analyzes symptoms, provides recommendations, and prioritizes focus areas. While the reports are not a substitute for licensed medical diagnosis, they offer a fast second opinion and complementary perspective to traditional healthcare. Users can take control of their health by accessing easy-to-understand reports that may help them identify potential health issues sooner.

Oncora Medical is an AI-powered platform that revolutionizes oncology care management. The platform offers a Clinical Data Platform for automating document generation and enhancing registry informatics. It provides AI-enabled case findings, revenue cycle management solutions, and cancer registry automation. Oncora's comprehensive AI solutions streamline workflows, improve outcomes, and capture revenue through intelligent automation. Trusted by top healthcare organizations worldwide, Oncora empowers healthcare organizations to achieve remarkable results in oncology care.

TORTUS is an AI application designed for doctors and clinicians, offering an AI interface for Electronic Health Records (EHR). It aims to provide faster, better, and kinder care by automating tasks such as record transcription, note generation, and clinical coding. The application is fully compliant with healthcare regulations and prioritizes data security. O.S.L.E.R. is positioned as a digital worker for digital work, enhancing patient outcomes and relieving clinician burnout through clinician-AI co-working.

Suki Assistant is an enterprise-grade AI assistant designed to help clinicians save time and focus on patient care. It offers ambient documentation, dictation, ICD-10 and HCC coding, and question answering capabilities. Suki has deep integrations with major EHR systems, ensuring seamless data flow. The AI is designed to prioritize safety and accuracy, with clinician-reviewed content before integration. Suki provides hassle-free partnerships, proven ROI, and advanced EHR integrations, making it a trusted choice for health systems nationwide.

The National Cancer Institute's Center for Biomedical Informatics and Information Technology (CBIIT) provides a comprehensive suite of tools, resources, and training to support cancer data science research. These resources include data repositories, analytical tools, data standards, and training materials. CBIIT also develops and maintains the NCI Thesaurus, a comprehensive vocabulary of cancer-related terms, and the Cancer Data Standards Registry and Repository (caDSR), a repository of cancer data standards. CBIIT's mission is to accelerate the pace of cancer research by providing researchers with the tools and resources they need to access, analyze, and share cancer data.

Radiology Business is an AI tool designed to provide insights and solutions for professionals in the radiology field. The platform covers a wide range of topics including management, imaging, technology, and conferences. It offers news, analysis, and resources to help radiologists stay informed and make informed decisions. Radiology Business aims to leverage artificial intelligence to improve workflow efficiency and enhance the overall experience in the radiology ecosystem.

Limbic is a clinical AI application designed for mental healthcare providers to save time, improve outcomes, and maximize impact. It offers a suite of tools developed by a team of therapists, physicians, and PhDs in computational psychiatry. Limbic is known for its evidence-based approach, safety focus, and commitment to patient care. The application leverages AI technology to enhance various aspects of the mental health pathway, from assessments to therapeutic content delivery. With a strong emphasis on patient safety and clinical accuracy, Limbic aims to support clinicians in meeting the rising demand for mental health services while improving patient outcomes and preventing burnout.

The Unlearn Platform is an AI-powered platform that streamlines clinical trials by creating digital twins of patients. It offers unparalleled precision in predicting clinical outcomes at future time points. The platform allows for designing smaller, more efficient studies, enhancing decision-making with digital twins, and identifying sensitive clinical outcomes. Unlearn.ai specializes in accelerating clinical development in various fields like neuroscience, immunology, and metabolic diseases.

Careo AI is an advanced AI-driven solution that is transforming clinical recruitment and revolutionizing healthcare staffing. The platform offers cutting-edge technology to streamline candidate management, vacancy tracking, workflow automation, analytics, and reporting. It provides seamless integration with existing systems, customization, and scalability for recruitment agencies. Careo AI aims to optimize recruitment strategies and enhance productivity in the healthcare industry.

AutoNotes is a leading healthcare AI Progress Note tool that offers AI-powered clinical documentation templates for generating SOAP Notes, DAP Notes, Treatment Plans, and more. It provides a user-friendly interface for therapists and healthcare professionals to create detailed and customizable clinical notes efficiently. With features like summarizing sessions, editing and downloading notes, and simple pricing plans, AutoNotes aims to streamline the documentation process in healthcare settings. The platform also offers advanced features like template customization, secure document storage, and dictation for voice-to-text conversion. Users can benefit from the platform's customization options, seamless integration with workflows, and responsive customer support.

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.

Taiyi (太一) is a bilingual large language model fine-tuned for diverse biomedical tasks. It aims to facilitate communication between healthcare professionals and patients, provide medical information, and assist in diagnosis, biomedical knowledge discovery, drug development, and personalized healthcare solutions. The model is based on the Qwen-7B-base model and has been fine-tuned using rich bilingual instruction data. It covers tasks such as question answering, biomedical dialogue, medical report generation, biomedical information extraction, machine translation, title generation, text classification, and text semantic similarity. The project also provides standardized data formats, model training details, model inference guidelines, and overall performance metrics across various BioNLP tasks.

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.

Kaapana is an open-source toolkit for state-of-the-art platform provisioning in the field of medical data analysis. The applications comprise AI-based workflows and federated learning scenarios with a focus on radiological and radiotherapeutic imaging. Obtaining large amounts of medical data necessary for developing and training modern machine learning methods is an extremely challenging effort that often fails in a multi-center setting, e.g. due to technical, organizational and legal hurdles. A federated approach where the data remains under the authority of the individual institutions and is only processed on-site is, in contrast, a promising approach ideally suited to overcome these difficulties. Following this federated concept, the goal of Kaapana is to provide a framework and a set of tools for sharing data processing algorithms, for standardized workflow design and execution as well as for performing distributed method development. This will facilitate data analysis in a compliant way enabling researchers and clinicians to perform large-scale multi-center studies. By adhering to established standards and by adopting widely used open technologies for private cloud development and containerized data processing, Kaapana integrates seamlessly with the existing clinical IT infrastructure, such as the Picture Archiving and Communication System (PACS), and ensures modularity and easy extensibility.

GPT4DFCI is a private and secure generative AI tool based on GPT-4, deployed for non-clinical use at Dana-Farber Cancer Institute. The tool is overseen by the Dana-Farber AI Governance Committee and developed by the Dana-Farber Informatics & Analytics Department. The repository includes manuscript & policy details, training material, front-end and back-end code, infrastructure information, API client for programmatic use, licensing details, and contact information.

Me LLaMA introduces a suite of open-source medical Large Language Models (LLMs), including Me LLaMA 13B/70B and their chat-enhanced versions. Developed through innovative continual pre-training and instruction tuning, these models leverage a vast medical corpus comprising PubMed papers, medical guidelines, and general domain data. Me LLaMA sets new benchmarks on medical reasoning tasks, making it a significant asset for medical NLP applications and research. The models are intended for computational linguistics and medical research, not for clinical decision-making without validation and regulatory approval.

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.

Scientific Large Language Models (Sci-LLMs) is a repository that collects papers on scientific large language models, focusing on biology and chemistry domains. It includes textual, molecular, protein, and genomic languages, as well as multimodal language. The repository covers various large language models for tasks such as molecule property prediction, interaction prediction, protein sequence representation, protein sequence generation/design, DNA-protein interaction prediction, and RNA prediction. It also provides datasets and benchmarks for evaluating these models. The repository aims to facilitate research and development in the field of scientific language modeling.

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.

The 'machine-learning-research' repository is a comprehensive collection of resources related to mathematics, machine learning, deep learning, artificial intelligence, data science, and various scientific fields. It includes materials such as courses, tutorials, books, podcasts, communities, online courses, papers, and dissertations. The repository covers topics ranging from fundamental math skills to advanced machine learning concepts, with a focus on applications in healthcare, genetics, computational biology, precision health, and AI in science. It serves as a valuable resource for individuals interested in learning and researching in the fields of machine learning and related disciplines.

ABigSurveyOfLLMs is a repository that compiles surveys on Large Language Models (LLMs) to provide a comprehensive overview of the field. It includes surveys on various aspects of LLMs such as transformers, alignment, prompt learning, data management, evaluation, societal issues, safety, misinformation, attributes of LLMs, efficient LLMs, learning methods for LLMs, multimodal LLMs, knowledge-based LLMs, extension of LLMs, LLMs applications, and more. The repository aims to help individuals quickly understand the advancements and challenges in the field of LLMs through a collection of recent surveys and research papers.

LLMs4TS is a repository focused on the application of cutting-edge AI technologies for time-series analysis. It covers advanced topics such as self-supervised learning, Graph Neural Networks for Time Series, Large Language Models for Time Series, Diffusion models, Mixture-of-Experts architectures, and Mamba models. The resources in this repository span various domains like healthcare, finance, and traffic, offering tutorials, courses, and workshops from prestigious conferences. Whether you're a professional, data scientist, or researcher, the tools and techniques in this repository can enhance your time-series data analysis capabilities.

2025-AI-College-Jobs is a repository containing a comprehensive list of AI/ML & Data Science jobs suitable for college students seeking internships or new graduate positions. The repository is regularly updated with positions posted within the last 120 days, featuring opportunities from various companies in the USA and internationally. The list includes positions in areas such as research scientist internships, quantitative research analyst roles, and other data science-related positions. The repository aims to provide a valuable resource for students looking to kickstart their careers in the field of artificial intelligence and machine learning.

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.

Awesome-TimeSeries-SpatioTemporal-LM-LLM is a curated list of Large (Language) Models and Foundation Models for Temporal Data, including Time Series, Spatio-temporal, and Event Data. The repository aims to summarize recent advances in Large Models and Foundation Models for Time Series and Spatio-Temporal Data with resources such as papers, code, and data. It covers various applications like General Time Series Analysis, Transportation, Finance, Healthcare, Event Analysis, Climate, Video Data, and more. The repository also includes related resources, surveys, and papers on Large Language Models, Foundation Models, and their applications in AIOps.

HuatuoGPT-o1 is a medical language model designed for advanced medical reasoning. It can identify mistakes, explore alternative strategies, and refine answers. The model leverages verifiable medical problems and a specialized medical verifier to guide complex reasoning trajectories and enhance reasoning through reinforcement learning. The repository provides access to models, data, and code for HuatuoGPT-o1, allowing users to deploy the model for medical reasoning tasks.

HuatuoGPT2 is an innovative domain-adapted medical large language model that excels in medical knowledge and dialogue proficiency. It showcases state-of-the-art performance in various medical benchmarks, surpassing GPT-4 in expert evaluations and fresh medical licensing exams. The open-source release includes HuatuoGPT2 models in 7B, 13B, and 34B versions, training code for one-stage adaptation, partial pre-training and fine-tuning instructions, and evaluation methods for medical response capabilities and professional pharmacist exams. The tool aims to enhance LLM capabilities in the Chinese medical field through open-source principles.

MOOSE 2.0 is a leaner, meaner, and stronger tool for 3D medical image segmentation. It is built on the principles of data-centric AI and offers a wide range of segmentation models for both clinical and preclinical settings. MOOSE 2.0 is also versatile, allowing users to use it as a command-line tool for batch processing or as a library package for individual processing in Python projects. With its improved speed, accuracy, and flexibility, MOOSE 2.0 is the go-to tool for segmentation tasks.

AI Hospital is a research repository focusing on the interactive evaluation and collaboration of Large Language Models (LLMs) as intern doctors for clinical diagnosis. The repository includes a simulation module tailored for various medical roles, introduces the Multi-View Medical Evaluation (MVME) Benchmark, provides dialog history documents of LLMs, replication instructions, performance evaluation, and guidance for creating intern doctor agents. The collaborative diagnosis with LLMs emphasizes dispute resolution. The study was authored by Zhihao Fan, Jialong Tang, Wei Chen, Siyuan Wang, Zhongyu Wei, Jun Xie, Fei Huang, and Jingren Zhou.

HL7-FHIR® expert for developers and healthcare data managers

Aids in informatics for nurses and midwives.

Medical engineer specializing in HL7/FHIR data conversion.

高血压临床决策支持

Comprehensive Guide in Clinical Trials & Regulations

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

I can assist doctors with information synthesis, medical literature reviews, patient education material, diagnostic guidelines, treatment options, ethical dilemmas, and staying updated on medical research and innovations.

Expert AI Doctor with up to date medical resources and textbooks to help improve your clinical skills.

Direct, insightful EEG and neurofeedback analysis specialist.

Accurate and timely matching of patients with clinical trials

Find active recruiting oncology clinical trials near you.

Expert in oncology trial matching, leveraging advanced GPT-4 Turbo techniques.

Explains clinical training at Tokamachi Hospital.

Clinical trial assistant answering questions about clinical trials.

Expert in creating tailored clinical psychology workshop presentations

Formally evaluates clinical cases against CDC/NHSN HAI surveillance definition criteria

Eyecare Clinical Assistant

Voice-to-text, Vision-to-text transcription, Transcript-to-‘Clinical format’ integrated with CDS. Writes clinical notes, referral letter, generate PDF,prepare discharge summary. (Ultimate aid for clinicians)

A therapist blending clinical methods with Eastern and Western philosophies.

Discuss AI and Theory of Mind with Clinical Psychologist Dr. Tamara Russel PHD and AI Expert Cris Ippolite