Best AI tools for< Clinical Decision Support >

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.

Wolters Kluwer is a global provider of professional information, software solutions, and services for various industries, including healthcare, tax and accounting, ESG, finance, compliance, and legal. The company's solutions combine domain expertise with advanced technology to help professionals make informed decisions, optimize processes, and achieve better outcomes. Wolters Kluwer's offerings include clinical decision support tools, tax and accounting software, ESG reporting solutions, regulatory compliance solutions, and legal research databases.

Medcol.io is a clinical AI assistant designed to support healthcare professionals in making informed decisions by providing evidence-based recommendations and insights. The platform leverages advanced algorithms and medical data analysis to assist in diagnosing diseases, suggesting treatment plans, and predicting patient outcomes. With a user-friendly interface and real-time updates, Medcol.io aims to streamline the clinical decision-making process and improve patient care.

Medical Brain is an AI-powered clinical assistant designed for both patients and providers. It engages with users to identify health risks and care gaps early, providing actionable insights and guidance to improve outcomes and intercept high-cost ER visits. The platform monitors patients 24/7, aggregates and understands all patient data, and generates real-time actions based on AI clinical decision support and automation. Medical Brain incorporates evidence-based best practices in various clinical modules and continuously learns from user experiences to enhance efficiency and intelligence.

RapidAI is a software platform powered by AI that focuses on aneurysm, pulmonary embolism, and stroke. It offers a range of products and solutions designed to improve patient care and efficiency in hospitals. The technology is clinically rooted and revolutionary, developed by clinicians for clinicians. RapidAI's AI-based platform is known for its speed, scalability, and security, with customization options to meet specific hospital needs. The platform has been trusted by 2,200 hospitals, impacting 90 million lives over 15 years of technological development.

Navina AI is a clinician-first AI platform designed to streamline patient care by providing key insights and actionable recommendations to healthcare providers, ACOs, MSOs, and health plans. The platform leverages proprietary AI technology to improve clinical decision-making, reduce administrative burden, and enhance quality management and risk adjustment processes. Navina AI offers efficient chart review, accurate risk adjustment, streamlined quality management, robust analytics, and a user-friendly interface that integrates seamlessly into the clinical workflow.

Notle is an advanced AI-driven psychometric recording tool designed for mental health professionals. It revolutionizes how patient interactions in psychotherapy sessions are captured and analyzed. The platform provides cutting-edge analysis, effortless tracking, in-depth metrics, and empowers clinicians with intelligent analytics for personalized care. Notle sets a new benchmark for psychometric evaluation tools, ensuring unrivaled precision in psychometric assessment. It offers advanced behavioral insights, user-friendly interface, unmatched precision & reliability, and non-invasive integration into healthcare practices. The application is reliable, accurate, impactful, and validated through research methods.

Regard is an AI-powered healthcare solution that automates clinical tasks, making it easier for clinicians to focus on patient care. It integrates with the EHR to analyze patient records and provide insights that can help improve diagnosis and treatment. Regard has been shown to improve hospital finances, patient safety, and physician happiness.

Sully.ai is the #1 all-in-one AI solution designed to save doctors' time by creating superhuman doctors. The platform offers a comprehensive set of features such as pre-visit screening, decision support, scribing, diagnosis assistance, clinical planning, and post-visit automations. Sully.ai is an automation platform that works seamlessly with Electronic Medical Records (EMR) systems, providing personalized and multilingual support for healthcare professionals. The AI model is HIPAA compliant and trained on real-life doctor encounters to enhance decision-making and streamline administrative tasks. With proven results in reducing repetitive tasks and improving efficiency, Sully.ai aims to transform healthcare delivery by empowering doctors to focus on patient care.

Qure AI is a leading healthcare AI application that offers AI-powered assistance for accelerated healthcare products impact. It provides evidence-based insights and solutions for lung, heart, neuro, and musculoskeletal conditions. Qure AI is designed to be a perfect collaborator in every care decision, with the ability to deploy and scale anywhere with best-in-class support. The application focuses on chest X-ray reporting, TB care cascades, lung nodule management, stroke and traumatic brain injury (TBI), musculoskeletal X-ray reporting, and heart failure.

Ada is a clinically driven AI application that supports better health outcomes and clinical excellence with intelligent technology. It provides users with trusted medical expertise in minutes to understand, manage, and get care for symptoms. Ada also offers powerful enterprise solutions to inform health decisions, enhance triage, and reduce avoidable costs. The application is optimized with human doctors and offers medical guidance in multiple languages, making it a popular choice for symptom assessment and pandemic responses.

SexpertAI is an AI-powered chatbot that provides comprehensive and accurate information on sexual health and relationships. It is designed to help users make informed decisions about their sexual health and well-being. SexpertAI is trained on a massive dataset of sexual health information, including medical research, clinical guidelines, and expert opinions. This allows it to provide users with up-to-date and evidence-based information on a wide range of sexual health topics, including STIs, contraception, pregnancy, and sexual dysfunction.

PMcardio is an AI-powered ECG interpretation platform that offers accurate diagnosis of cardiovascular diseases within seconds. It provides rapid referral to specialists, detects occlusion myocardial infarction, and identifies reduced left ventricular ejection fraction from 12-lead ECGs. PMcardio enhances clinical decision-making, standardizes ECG reports, and ensures data security. The platform is designed for both individuals and organizations in the healthcare sector, offering seamless coordination and high accuracy in diagnostics.

Intelligencia AI is a leading provider of AI-powered solutions for the pharmaceutical industry. Our suite of solutions helps de-risk and enhance clinical development and decision-making. We use a combination of data, AI, and machine learning to provide insights into the probability of success for drugs across multiple therapeutic areas. Our solutions are used by many of the top global pharmaceutical companies to improve their R&D productivity and make more informed decisions.

Unlearn.ai is an AI-powered digital twins solution provider that optimizes clinical trials. Their TwinRCTs enable confident and quick clinical trials in various medical fields such as neuroscience, immunology, and metabolic diseases. By creating digital twins of patients, Unlearn.ai enhances the power and efficiency of clinical trials, attracting study participants and making confident decisions from early to late-stage studies.

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.

HealthITAnalytics is a leading source of news, insights, and analysis on the use of information technology in healthcare. The website covers a wide range of topics, including artificial intelligence, machine learning, data analytics, and population health management. HealthITAnalytics also provides resources for healthcare professionals, such as white papers, webinars, and podcasts.

NeuProScan is an AI platform designed for the early detection of pre-clinical Alzheimer's from MRI scans. It utilizes AI technology to predict the likelihood of developing Alzheimer's years in advance, helping doctors improve diagnosis accuracy and optimize the use of costly PET scans. The platform is fully customizable, user-friendly, and can be run on devices or in the cloud. NeuProScan aims to provide patients and healthcare systems with valuable insights for better planning and decision-making.

Intelligent Health is the world's leading AI in medicine summit series dedicated to saving lives with AI. The platform hosts a healthtech community committed to advancing pivotal conversations on AI in medicine and fostering global collaboration across the healthcare sector. With a comprehensive agenda offering access to expert voices, Intelligent Health expedites critical discussions on challenges, solutions, and innovations to facilitate key decision-making and impactful investments. The platform aims to ensure the safe, effective, and democratic adoption of AI in healthcare to improve global health outcomes for all.

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.

This repository is a curated collection of resources for fine-tuning Large Language Models (LLMs) like GPT, BERT, RoBERTa, and their variants. It includes tutorials, papers, tools, frameworks, and best practices to aid researchers, data scientists, and machine learning practitioners in adapting pre-trained models to specific tasks and domains. The resources cover a wide range of topics related to fine-tuning LLMs, providing valuable insights and guidelines to streamline the process and enhance model performance.

Python package for concise, transparent, and accurate predictive modeling. All sklearn-compatible and easy to use. _For interpretability in NLP, check out our new package:imodelsX _

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.

InterpretML is an open-source package that incorporates state-of-the-art machine learning interpretability techniques under one roof. With this package, you can train interpretable glassbox models and explain blackbox systems. InterpretML helps you understand your model's global behavior, or understand the reasons behind individual predictions. Interpretability is essential for: - Model debugging - Why did my model make this mistake? - Feature Engineering - How can I improve my model? - Detecting fairness issues - Does my model discriminate? - Human-AI cooperation - How can I understand and trust the model's decisions? - Regulatory compliance - Does my model satisfy legal requirements? - High-risk applications - Healthcare, finance, judicial, ...

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.

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.

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.

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.

A repository that lists papers related to Large Language Model (LLM) based agents. The repository covers various topics including survey, planning, feedback & reflection, memory mechanism, role playing, game playing, tool usage & human-agent interaction, benchmark & evaluation, environment & platform, agent framework, multi-agent system, and agent fine-tuning. It provides a comprehensive collection of research papers on LLM-based agents, exploring different aspects of AI agent architectures and applications.

This repository contains a collection of papers and resources related to Large Language Models (LLMs), including their applications in various domains such as text generation, translation, question answering, and dialogue systems. The repository also includes discussions on the ethical and societal implications of LLMs. **Description** This repository is a collection of papers and resources related to Large Language Models (LLMs). LLMs are a type of artificial intelligence (AI) that can understand and generate human-like text. They have a wide range of applications, including text generation, translation, question answering, and dialogue systems. **For Jobs** - **Content Writer** - **Copywriter** - **Editor** - **Journalist** - **Marketer** **AI Keywords** - **Large Language Models** - **Natural Language Processing** - **Machine Learning** - **Artificial Intelligence** - **Deep Learning** **For Tasks** - **Generate text** - **Translate text** - **Answer questions** - **Engage in dialogue** - **Summarize text**

This repository does not provide a tool, but rather a collection of resources and strategies for academics in the field of artificial intelligence who are feeling depressed or overwhelmed by the rapid advancements in the field. The resources include articles, blog posts, and other materials that offer advice on how to cope with the challenges of working in a fast-paced and competitive environment.

LLM4IR-Survey is a collection of papers related to large language models for information retrieval, organized according to the survey paper 'Large Language Models for Information Retrieval: A Survey'. It covers various aspects such as query rewriting, retrievers, rerankers, readers, search agents, and more, providing insights into the integration of large language models with information retrieval systems.

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.

KG-LLM-Papers is a repository that collects papers integrating knowledge graphs (KGs) and large language models (LLMs). It serves as a comprehensive resource for research on the role of KGs in the era of LLMs, covering surveys, methods, and resources related to this integration.

GPT for AI in Medicine

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Aids in informatics for nurses and midwives.

An academic assistant for psychiatrists, creating educational content and practice questions. (Not for use in clinical decision making, verify all information, as model may produce errors)

ポケット産科麻酔指導医

Your go-to virtual companion for understanding medical conditions, treatments, and wellness tips! Empowers you with knowledge for informed health decisions. 🚑📚

Scientific expert in evaluating articles using ROBINS-I and Cochrane tools

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