Best AI tools for< Healthcare Informaticist >

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

The Medical Futurist is a digital health and AI-focused media platform that provides insights, research, and educational resources to healthcare professionals and industry leaders. It covers topics such as artificial intelligence in medicine, the future of pharma, and emerging trends in digital health. The platform also offers keynote speeches, courses, and e-books on these topics.

Consensus is a healthcare interoperability platform that simplifies data exchange and document processing through artificial intelligence technologies. It offers solutions for clinical documentation, HIPAA compliance, natural language processing, and robotic process automation. Consensus enables secure and efficient data exchange among healthcare providers, insurers, and other stakeholders, improving care coordination and operational efficiency.

ZeOmega is an AI-powered healthcare solutions platform that offers population health analytics, care management, benefits administration, and operational efficiency. It provides a comprehensive set of practical, AI-powered solutions for various healthcare stakeholders, including health plans, health systems, Medicare, Medicaid, and ACOs. ZeOmega's platform integrates data to create a single source of truth, drives intelligent automation, and optimizes quality of care through AI-powered insights and automated workflows. The platform is designed to streamline operations, improve efficiency, and enhance the overall quality of healthcare services.

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.

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.

Hyro is a conversational AI platform designed for enterprise use, specifically in the healthcare industry. It offers a full-stack conversational AI omnichannel solution that includes AI assistants for repetitive tasks, call center automation, conversational intelligence, and responsible AI deployment. Hyro's platform integrates with popular tools like Epic EMR, Salesforce, and Cisco to streamline workflows and improve patient engagement. The platform is known for its adaptive communications capabilities, instant FAQ resolution, and IT help desk support. With a focus on responsible AI, Hyro aims to optimize decision-making and enhance patient support while reducing operational costs and improving efficiency.

Thoughtful is an AI-powered revenue cycle automation platform that offers efficiency reports, eligibility verification, patient intake automation, claims processing, and more. It deploys AI across healthcare organizations to maximize profitability, reduce errors, and enhance operational excellence. Thoughtful's AI agents work tirelessly, 10x more efficiently than humans, and never get tired. The platform helps providers improve revenue cycle management, financial health, HR processes, and healthcare IT operations through seamless integration, reduced overhead, and significant performance improvements. Thoughtful offers a white-glove service, custom-built platform, seamless integration with all healthcare applications, and performance-based contracting with refund and value guarantees.

ClosedLoop is a healthcare data science platform that helps organizations improve outcomes and reduce unnecessary costs with accurate, explainable, and actionable predictions of individual-level health risks. The platform provides a comprehensive library of easily modifiable templates for healthcare-specific predictive models, machine learning (ML) features, queries, and data transformation, which accelerates time to value. ClosedLoop's AI/ML platform is designed exclusively for the data science needs of modern healthcare organizations and helps deliver measurable clinical and financial impact.

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.

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.

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.

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.

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.

This repository is dedicated to summarizing papers related to large language models with the field of law. It includes applications of large language models in legal tasks, legal agents, legal problems of large language models, data resources for large language models in law, law LLMs, and evaluation of large language models in the legal domain.

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.

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.

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.

This repository, Awesome-LLM-Survey, serves as a comprehensive collection of surveys related to Large Language Models (LLM). It covers various aspects of LLM, including instruction tuning, human alignment, LLM agents, hallucination, multi-modal capabilities, and more. Researchers are encouraged to contribute by updating information on their papers to benefit the LLM survey community.

This tool is designed to detect and classify Alzheimer's Disease using Deep Learning and Machine Learning algorithms on an early basis, which is further optimized using the Crow Search Algorithm (CSA). Alzheimer's is a fatal disease, and early detection is crucial for patients to predetermine their condition and prevent its progression. By analyzing MRI scanned images using Artificial Intelligence technology, this tool can classify patients who may or may not develop AD in the future. The CSA algorithm, combined with ML algorithms, has proven to be the most effective approach for this purpose.

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.

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.

The AWS Healthcare and Life Sciences AI/ML Immersion Day workshops provide hands-on experience for customers to learn about AI/ML services, gain a deep understanding of AWS AI/ML services, and understand best practices for using AI/ML in the context of HCLS applications. The workshops cater to individuals at all levels, from machine learning experts to developers and managers, and cover topics such as training, testing, MLOps, deployment practices, and software development life cycle in the context of AI/ML. The repository contains notebooks that can be used in AWS Instructure-Led Labs or self-paced labs, offering a comprehensive learning experience for integrating AI/ML into applications.

Cyclops is a toolkit for facilitating research and deployment of ML models for healthcare. It provides a few high-level APIs namely: data - Create datasets for training, inference and evaluation. We use the popular 🤗 datasets to efficiently load and slice different modalities of data models - Use common model implementations using scikit-learn and PyTorch tasks - Use common ML task formulations such as binary classification or multi-label classification on tabular, time-series and image data evaluate - Evaluate models on clinical prediction tasks monitor - Detect dataset shift relevant for clinical use cases report - Create model report cards for clinical ML models

The Microsoft Health Intelligence Machine Learning Toolbox is a repository that provides low-level and high-level building blocks for Machine Learning / AI researchers and practitioners. It simplifies and streamlines work on deep learning models for healthcare and life sciences by offering tested components such as data loaders, pre-processing tools, deep learning models, and cloud integration utilities. The repository includes two Python packages, 'hi-ml-azure' for helper functions in AzureML, 'hi-ml' for ML components, and 'hi-ml-cpath' for models and workflows related to histopathology images.

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.

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.

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.

HL7-FHIR® expert for developers and healthcare data managers

Medical engineer specializing in HL7/FHIR data conversion.

Aids in informatics for nurses and midwives.

Provides info on Kerala's healthcare facilities.

Insights on AI in healthcare and wellness

高血压临床决策支持

Guide to healthcare services in India.

Leading in Smart Healthcare AI, Powered by OpenAI

A navigator for finding healthcare services and scheduling appointments.

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

I can help you with healthcare UX design

Healthcare futurist discussing trends, innovations, and predictions, inspired by space, resilience, and precision medicine.

Expert in healthcare claim appeals

Healthcare Coordination AI Assistant

A guide on healthcare legal planning

Simply type "news" for easy to digest updates in the Healthcare industry, or be as specific as you want and get the top healthcare news from reliable sources. Healthtech, patient care, insurance policies, provider networks, value based care, behavioral health, condition management, therapy.

Friendly assistant for healthcare and welfare.

Guides through healthcare app legalities

Professional advice for healthcare managers

Guiding healthcare conversations with insights.