Best AI tools for< Healthcare Researcher >

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.

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.

OpenAI01.net is an AI tool that offers free usage with some limitations. It provides a new series of AI models designed to spend more time thinking before responding, capable of reasoning through complex tasks and solving harder problems in science, coding, and math. Users can ask questions and get answers for free, with the option to select different models based on credits. The tool excels in complex reasoning tasks and has shown impressive performance in various benchmarks.

Vizly is an AI-powered data analysis tool that empowers users to make the most of their data. It allows users to chat with their data, visualize insights, and perform complex analysis. Vizly supports various file formats like CSV, Excel, and JSON, making it versatile for different data sources. The tool is free to use for up to 10 messages per month and offers a student discount of 50%. Vizly is suitable for individuals, students, academics, and organizations looking to gain actionable insights from their data.

Image Bear AI is an advanced image recognition tool that utilizes artificial intelligence to analyze and identify objects within images. The application is designed to assist users in various industries such as e-commerce, security, and healthcare by providing accurate and efficient image analysis capabilities. With its cutting-edge technology, Image Bear AI offers a user-friendly interface and fast processing speeds, making it a valuable tool for businesses looking to streamline their image recognition processes.

GaitAnalyzer.health is a web application designed to analyze and assess human gait patterns for healthcare professionals and researchers. The platform utilizes advanced algorithms to process gait data captured through various sensors and devices, providing valuable insights into gait abnormalities and biomechanical characteristics. Users can upload gait data, visualize results, and generate detailed reports to aid in diagnosis and treatment planning. GaitAnalyzer.health aims to improve the understanding of human movement patterns and enhance the quality of care in the field of biomechanics and rehabilitation.

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.

Modality.AI is an AI application that has developed an automated, clinically validated system to assess neurological and psychiatric states both in clinic and remotely. The platform utilizes conversational AI to monitor conditions accurately and consistently, allowing researchers and clinicians to review data in near real-time and monitor treatment response over time. Modality.AI collaborates with world-class AI/Machine Learning experts and leading institutions to provide a HIPAA-compliant system for assessing various indications such as ALS, Parkinson's, depression, autism, Huntington's Disease, schizophrenia, and mild cognitive impairment. The platform enables convenient monitoring at home through streaming and analysis of speech and facial responses, without the need for special software or apps. Modality.AI is accessible on various devices with a browser, webcam, and microphone, offering a new approach to efficient and cost-effective clinical trials.

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.

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.

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.

CompliantChatGPT is a HIPAA-compliant platform that allows users to utilize OpenAI's GPT models for healthcare-related tasks while maintaining data privacy and security. It anonymizes protected health information (PHI) by replacing it with tokens, ensuring compliance with HIPAA regulations. The platform offers various modes tailored to specific healthcare needs, including bloodwork analysis, PHI anonymization, diagnosis assistance, and treatment planning. CompliantChatGPT streamlines healthcare tasks, enhances productivity, and provides user-friendly assistance through its intuitive interface.

Doctronic Concierge is a state-of-the-art AI-powered health assistant that offers fully personalized medical care. It revolutionizes healthcare by providing tailored care through learning from every interaction. Users can secure their spot for free to experience the future of healthcare with the world's first personalized medical AI.

K Health is an AI-powered healthcare platform that leverages artificial intelligence to provide users with personalized medical insights and advice. By analyzing symptoms and medical history, K Health offers users a quick and convenient way to assess their health conditions and receive recommendations for next steps. The platform aims to democratize healthcare by making medical expertise more accessible and affordable to a wider audience. K Health is designed to complement traditional healthcare services and empower individuals to take control of their health proactively.

The website OpenLife.ai is an AI tool that focuses on various aspects of healthcare, including medical AI, ambient clinical intelligence, clinical documentation integrity, healthcare analytics, patient engagement, radiology solutions, and more. It offers insights, news, and resources related to the application of artificial intelligence in the healthcare industry.

Grafi AI is an AI tool designed to generate accurate healthcare content in minutes by leveraging databases, scientific journals, and user-provided content. It allows healthcare professionals to create quality, long-form content quickly and easily, reducing the burden of fact validation and enabling the generation of personalized, SEO-friendly content. Users can upload their own documents and references to train the AI algorithm and produce content tailored to their expertise.

Simbo AI is a Gen AI platform designed for healthcare enterprises, offering autonomous applications for medical practice automation. It combines LLM and symbolic knowledge bases to provide hallucination-free responses. The platform is fully controllable, consistent, secure, and responsible, ensuring accurate and reliable AI interactions. Simbo AI utilizes Symbolic RAG technology with Lossless NLU for exact search and fact-checking capabilities. It aims to automate medical practices, reduce costs, and improve patient care, ultimately enhancing the lives of doctors and patients.

Cercle is an AI platform that advances healthcare for women by transforming healthcare data into real-time, high-quality insights. The platform caters to women's healthcare providers, payors, and pharma companies, helping them run more efficient businesses and provide personalized care. Cercle's Biomedical Graph unlocks insights at unprecedented speed and accuracy, optimizing patient care and improving outcomes in areas such as assisted reproduction and fertility processes.

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.

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

The 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.

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

Apollo is a multilingual medical LLM that covers English, Chinese, French, Hindi, Spanish, Hindi, and Arabic. It is designed to democratize medical AI to 6B people. Apollo has achieved state-of-the-art results on a variety of medical NLP tasks, including question answering, medical dialogue generation, and medical text classification. Apollo is easy to use and can be integrated into a variety of applications, making it a valuable tool for healthcare professionals and researchers.

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.

MONAI is a PyTorch-based, open-source framework for deep learning in healthcare imaging. It provides a comprehensive set of tools for medical image analysis, including data preprocessing, model training, and evaluation. MONAI is designed to be flexible and easy to use, making it a valuable resource for researchers and developers in the field of medical imaging.

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.

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.

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.

ai-collective-tools is an open-source community dedicated to creating a comprehensive collection of AI tools for developers, researchers, and enthusiasts. The repository provides a curated selection of AI tools and resources across various categories such as 3D, Agriculture, Art, Audio Editing, Avatars, Chatbots, Code Assistant, Cooking, Copywriting, Crypto, Customer Support, Dating, Design Assistant, Design Generator, Developer, E-Commerce, Education, Email Assistant, Experiments, Fashion, Finance, Fitness, Fun Tools, Gaming, General Writing, Gift Ideas, HealthCare, Human Resources, Image Classification, Image Editing, Image Generator, Interior Designing, Legal Assistant, Logo Generator, Low Code, Models, Music, Paraphraser, Personal Assistant, Presentations, Productivity, Prompt Generator, Psychology, Real Estate, Religion, Research, Resume, Sales, Search Engine, SEO, Shopping, Social Media, Spreadsheets, SQL, Startup Tools, Story Teller, Summarizer, Testing, Text to Speech, Text to Image, Transcriber, Travel, Video Editing, Video Generator, Weather, Writing Generator, and Other Resources.

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 contains a curated list of resources on generative information retrieval, including research papers, datasets, tools, and applications. Generative information retrieval is a subfield of information retrieval that uses generative models to generate new documents or passages of text that are relevant to a given query. This can be useful for a variety of tasks, such as question answering, summarization, and document generation. The resources in this repository are intended to help researchers and practitioners stay up-to-date on the latest advances in generative information retrieval.

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.

Welcome to the ultimate hub for on-device Large Language Models (LLMs)! This repository is your go-to resource for all things related to LLMs designed for on-device deployment. Whether you're a seasoned researcher, an innovative developer, or an enthusiastic learner, this comprehensive collection of cutting-edge knowledge is your gateway to understanding, leveraging, and contributing to the exciting world of on-device LLMs.

The W3C Cognitive AI Community Group focuses on advancing Cognitive AI through collaboration on defining use cases, open source implementations, and application areas. The group aims to demonstrate the potential of Cognitive AI in various domains such as customer services, healthcare, cybersecurity, online learning, autonomous vehicles, manufacturing, and web search. They work on formal specifications for chunk data and rules, plausible knowledge notation, and neural networks for human-like AI. The group positions Cognitive AI as a combination of symbolic and statistical approaches inspired by human thought processes. They address research challenges including mimicry, emotional intelligence, natural language processing, and common sense reasoning. The long-term goal is to develop cognitive agents that are knowledgeable, creative, collaborative, empathic, and multilingual, capable of continual learning and self-awareness.

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.

OpenAGI is a framework designed to make the development of autonomous human-like agents accessible to all. It aims to pave the way towards open agents and eventually AGI for everyone. The initiative strongly believes in the transformative power of AI and offers developers a platform to create autonomous human-like agents. OpenAGI features a flexible agent architecture, streamlined integration and configuration processes, and automated/manual agent configuration generation. It can be used in education for personalized learning experiences, in finance and banking for fraud detection and personalized banking advice, and in healthcare for patient monitoring and disease diagnosis.

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.

AI-resources is a repository containing links to various resources for learning Artificial Intelligence. It includes video lectures, courses, tutorials, and open-source libraries related to deep learning, reinforcement learning, machine learning, and more. The repository categorizes resources for beginners, average users, and advanced users/researchers, providing a comprehensive collection of materials to enhance knowledge and skills in AI.

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.

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.

Provides info on Kerala's healthcare facilities.

Leading in Smart Healthcare AI, Powered by OpenAI

Expert and respectful guide on aging research and its societal impacts.

Insights on AI in healthcare and wellness

Guiding healthcare conversations with insights.

Chinese biopharma, healthcare, policy, and industrial park analysis expert.

A virtual doctor for cognitive assessment.

Analyzes CME evaluation data for insights.

Neurologist with a humorous, educational twist.

高血压临床决策支持

This GPT is instructed to give answers from all the information it has about the disease and expects the user to do their due diligence.

GPT for AI in Medicine

Explores emerging trends and innovations in medicine.

Information on male menopause, providing insights and explanations.

Inquisitive medical advisor.

This prompt is presented as a virtual health assistant that interacts empathically and efficiently with the user, assuming the role of a doctor.

「痛みを経験する前に考える」または「痛みを経験してから考える」を分析する

Formal health assistant with data upload for personalized monitoring.

Informative guide on lymphoma, covering classification and treatments.

Provides medically-informed insights on breast cancer.