Best AI tools for< Health Informatics Specialist >

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.

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.

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 in one solution. Suki has deep integrations with major EHR systems, ensuring seamless data flow and clinician-reviewed content. The AI is designed to minimize risks of bias and hallucinations, with SOC2 Type 2 and HIPAA compliance. Suki serves large health systems, providing hassle-free partnerships and proven ROI within a short period. It offers advanced EHR integrations, bidirectional capabilities, and ultimate convenience for clinicians.

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.

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.

The Human-Centred Artificial Intelligence Lab (Holzinger Group) is a research group focused on developing AI solutions that are explainable, trustworthy, and aligned with human values, ethical principles, and legal requirements. The lab works on projects related to machine learning, digital pathology, interactive machine learning, and more. Their mission is to combine human and computer intelligence to address pressing problems in various domains such as forestry, health informatics, and cyber-physical systems. The lab emphasizes the importance of explainable AI, human-in-the-loop interactions, and the synergy between human and machine intelligence.

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.

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.

Element5 is an intelligent post-acute workflow automation platform that offers solutions for authorization, eligibility, and revenue cycle management. It leverages AI-driven automation to accelerate speed to care, optimize financial outcomes, and create staff capacity. The platform is trusted by industry leaders for transforming post-acute operations and improving efficiency by automating administrative processes.

Lyrebird Health is an AI-powered medical scribe that automates documentation tasks for healthcare providers. It uses natural language processing (NLP) to listen in on patient encounters and generate accurate, medico-legally compliant notes, letters, and assessments. Lyrebird Health is designed to save clinicians time and reduce burnout, allowing them to focus on providing better care to their patients.

Yesil Health is an AI Health Assistant application that provides evidence-based answers to health questions. Users can chat for free to receive personalized health information, analyze health PDFs, and get accurate explanations based on the latest medical research. The application learns about users with each question, building a personalized health profile. Yesil Health is backed by innovative AI technology and aims to enhance individuals' well-being through data-driven insights for a healthier lifestyle.

Olivia is a health application designed to simplify and personalize your health journey. It helps users manage their health data, connect with healthcare providers, and track their health metrics. Olivia's AI-enabled assistant provides personalized support by summarizing medical records, answering questions about medical guidelines, and offering insights on conditions and treatments. The application aims to alleviate the burden of managing health information and empower users to receive the best care possible.

Iodine Software is a healthcare technology company that provides AI-enabled solutions for revenue cycle management, clinical documentation integrity, and utilization management. The company's flagship product, AwareCDI, is a suite of solutions that addresses the root causes of mid-cycle revenue leakage from admission through post-billing review. AwareCDI uses Iodine's CognitiveML AI engine to spot what is missing in patient documentation based on clinical evidence. This enables healthcare organizations to maximize documentation integrity and revenue capture. Iodine Software also offers AwareUM, a continuous, intelligent prioritization solution for peak UM performance.

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.

Sunoh is a medical AI scribe that uses ambient listening technology to convert natural conversations between healthcare providers and patients into clinical documentation. It offers a unique and immersive experience for both doctors and patients, making the documentation of clinical notes faster and more efficient than ever before. Sunoh can be used with your EHR to accelerate your documentation.

The EMR Software is an AI-powered application designed to streamline healthcare practices by integrating future technologies for accurate outcomes and enhanced care. It offers innovative features such as natural language processing, AI-powered assistant, task automation, and radiology image enhancement. The software aims to reduce medical costs, improve turnover rates, increase medical efficiency, and enhance patient retention rates. It provides data security, clinical management, e-billing processes, revenue management, and tele-monitoring. EMR Software assists in managing clients effortlessly, improving billing operations, maximizing hospital profits, consulting patients remotely, and tracking chronic disease progression.

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.

Rapid Claims AI is an autonomous medical coding and documentation solution powered by AI technology. It aims to streamline medical coding operations, reduce administrative costs, improve reimbursements, and ensure compliance for healthcare providers. The platform offers features like automated coding, personalized solutions, actionable insights, and customizable AI rule sets. Rapid Claims AI is designed to seamlessly integrate into existing workflows, catering to various healthcare setups and specialties. The application prioritizes security and privacy, with data encryption and secure cloud storage. It serves as a valuable tool for enhancing revenue cycle management processes in the healthcare industry.

The Azure Health Data and AI Samples Repo is a collection of sample apps and code to help users start with Azure Health Data and AI services, learn product usage, and speed up implementations. It includes samples for various health data workflows, such as data ingestion, analytics, machine learning, SMART on FHIR, patient services, FHIR service integration, Azure AD B2C access, DICOM service, MedTech service, and healthcare data solutions in Microsoft Fabric. These samples are simplified scenarios for testing purposes only.

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.

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.

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.

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.

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.

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.

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-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.

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.

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.

OpenHealth is an AI health assistant that helps users manage their health data by leveraging AI and personal health information. It allows users to consolidate health data, parse it smartly, and engage in contextual conversations with GPT-powered AI. The tool supports various data sources like blood test results, health checkup data, personal physical information, family history, and symptoms. OpenHealth aims to empower users to take control of their health by combining data and intelligence for actionable health management.

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.

HF-Waitress is a powerful server application for deploying and interacting with HuggingFace Transformer models. It simplifies running open-source Large Language Models (LLMs) locally on-device, providing on-the-fly quantization via BitsAndBytes, HQQ, and Quanto. It requires no manual model downloads, offers concurrency, streaming responses, and supports various hardware and platforms. The server uses a `config.json` file for easy configuration management and provides detailed error handling and logging.

Multi-Agent Orchestrator is a flexible and powerful framework for managing multiple AI agents and handling complex conversations. It intelligently routes queries to the most suitable agent based on context and content, supports dual language implementation in Python and TypeScript, offers flexible agent responses, context management across agents, extensible architecture for customization, universal deployment options, and pre-built agents and classifiers. It is suitable for various applications, from simple chatbots to sophisticated AI systems, accommodating diverse requirements and scaling efficiently.

OneKE is a flexible dockerized system for schema-guided knowledge extraction, capable of extracting information from the web and raw PDF books across multiple domains like science and news. It employs a collaborative multi-agent approach and includes a user-customizable knowledge base to enable tailored extraction. OneKE offers various IE tasks support, data sources support, LLMs support, extraction method support, and knowledge base configuration. Users can start with examples using YAML, Python, or Web UI, and perform tasks like Named Entity Recognition, Relation Extraction, Event Extraction, Triple Extraction, and Open Domain IE. The tool supports different source formats like Plain Text, HTML, PDF, Word, TXT, and JSON files. Users can choose from various extraction models like OpenAI, DeepSeek, LLaMA, Qwen, ChatGLM, MiniCPM, and OneKE for information extraction tasks. Extraction methods include Schema Agent, Extraction Agent, and Reflection Agent. The tool also provides support for schema repository and case repository management, along with solutions for network issues. Contributors to the project include Ningyu Zhang, Haofen Wang, Yujie Luo, Xiangyuan Ru, Kangwei Liu, Lin Yuan, Mengshu Sun, Lei Liang, Zhiqiang Zhang, Jun Zhou, Lanning Wei, Da Zheng, and Huajun Chen.

AIDA64CRCK is a tool designed for Windows users to access the latest version for free. It provides users with comprehensive system information and diagnostics to optimize their computer performance. The tool is user-friendly and offers detailed insights into hardware components, software configurations, and system stability. With AIDA64CRCK, users can easily monitor their system health and troubleshoot any issues that may arise, making it a valuable utility for both casual users and tech enthusiasts.

LLM-Geo is an AI-powered geographic information system (GIS) that leverages Large Language Models (LLMs) for automatic spatial data collection, analysis, and visualization. By adopting LLM as the reasoning core, it addresses spatial problems with self-generating, self-organizing, self-verifying, self-executing, and self-growing capabilities. The tool aims to make spatial analysis easier, faster, and more accessible by reducing manual operation time and delivering accurate results through case studies. It uses GPT-4 API in a Python environment and advocates for further research and development in autonomous GIS.

Nephrology expert providing detailed kidney health information.

Nutritionists and Dietitians handle health information, dietary preferences, and personal goals of clients, these professionals must ensure the confidentiality and security of this data.

Portuguese OCR for medical test coding, outputs in table format.

Specialist in vision care, offering eye health tips and information on eye conditions.

Informative guide on menopause, offering support.

Expert on Kangen water, creating informative content and addressing queries.

Informative guide on asbestos hazards and removal

Non-judgemental drug harm reduction assistant providing safe usage and interaction info.

Especialista em dados de Saúde Coletiva

A Neurologist GPT Specializing in Brain Health, Aging, and Dementia Prevention.

Agente especializado en Logoterapia y Viktor Frankl, informativo y respetuoso.

Medical engineer specializing in HL7/FHIR data conversion.

Veterans Benefits Navigator (VBN) is a specialized chatbot designed to guide U.S. veterans through the complexities of VA benefits. It offers tailored, up-to-date information, locates nearest VA facilities, and ensures empathetic, confidential assistance for all benefit-related inquiries.

Aids in informatics for nurses and midwives.

Provides information on digestive health and stomach issues, in an informative tone.

Insurance providers collect and process personal health, financial, and property information, making it crucial to implement comprehensive data protection strategies.

Adolescent health guide with comparative tables and tips.

Direct and clear health alerts with consistent tone.

Analyzing global health data for pandemic prediction and strategy.

Fitness and Wellness Centers collect personal health and fitness data of their clients, including potentially sensitive health metrics, requiring careful handling and protection of this data.