Best AI tools for< Generate Clinical Reports >

Yseop offers Natural Language Generation (NLG) services that automate and translate data into actionable language, simplifying complex workflows. Its AI-based technologies generate core elements of specialist medical reports, including clinical study reports (CSR), patient narratives, and more. Yseop also automates the writing of financial reports, removing the risk of error in manual writing to ensure accuracy, consistency, and compliance. Additionally, Yseop provides bespoke NLG applications tailored to specific needs, helping streamline operations and empower workers with tailored information and insights.

Everbility is an AI-powered clinical documentation tool designed for Allied Health Professionals. It helps in writing reports, synthesizing client notes, brainstorming ideas, and focusing on client care. The tool saves time by generating progress notes, letters, and assessment reports, while ensuring data privacy and compliance with regulations like HIPAA and Australian Privacy Principles.

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.

AKASA is a healthcare revenue cycle management company that uses generative AI (GenAI) to improve the revenue cycle for healthcare providers. AKASA's GenAI-powered platform and solutions help healthcare providers reduce denials, improve margins, and increase revenue. AKASA's platform includes solutions for authorization management, claim status, and claim attachment. AKASA's GenAI is trained on clinical and financial data and is optimized for healthcare. AKASA's clients include over 475 hospitals and 6,500 outpatient facilities across all 50 states.

Insight is an AI-powered medical research tool that serves as a research assistant for generating scientific summaries, hypotheses, experimental designs, and target identification. It empowers scientists to navigate literature, formulate hypotheses, and design experiments by utilizing peer-reviewed databases to provide reliable outputs. With integrated features like NIH PubMed access, NIH Reporter insights, and MYGENE & MYVARIANT deep dives, Insight streamlines the research process and accelerates discoveries in the medical field.

MDHub is a clinical AI assistant designed to support behavioral health clinicians in their practice. It offers a user-friendly interface for seamless integration into workflows, time-saving features like instant audio transformation for charting, and personalized treatment plan recommendations. The application aims to enhance patient care by automating documentation tasks and improving efficiency in mental health practices.

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.

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.

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

Heidi is an AI-powered medical scribe that helps clinicians save time and improve patient care. It uses natural language processing to capture every detail of a patient visit, and then automatically generates a note that is tailored to the clinician's preferences. Heidi can also be used to create letters, add billing codes, and generate patient summaries. It is trusted by clinicians and healthcare staff in over 35 countries.

Astra Health is a leading multilingual AI assistant designed for clinicians to automate clinical documentation, empower clinicians with medical notes creation solutions using generative AI, and provide features like ambient listening mode, instant notes generation, and custom templates. The application is trusted by thousands of clinicians and is known for its ethical and safe practices in data security. Astra Health AI has transformed clinical note-taking, allowing clinicians to focus more on patient care and improve efficiency in consultations.

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.

Neural Consult is a cutting-edge AI-powered medical education platform that offers personalized learning tools to empower medical students. The platform provides unlimited board questions, Anki cards, clinical simulations, and more, tailored to individual study needs. With features like question generation, lecture summaries, differential diagnosis, and AI-powered case simulations, Neural Consult revolutionizes the way medical students learn and prepare for exams. Trusted by students at top medical schools, Neural Consult aims to enhance clinical reasoning, memorization skills, and overall learning efficiency through innovative AI technology.

Oatmeal Health is an AI-enabled platform that focuses on cancer screening and clinical trials. The platform seamlessly integrates AI technology with dedicated on-site and virtual care teams to provide evidence-based cancer screening models for Community Health Centers. Oatmeal Health aims to improve patient health, lower the overall cost of cancer care, and generate revenue through fee-for-service and value-based reimbursements. The platform offers AI risk assessments, care navigation, and advanced diagnostic screenings to support patients and track outcomes, ultimately aiming for early cancer detection and saving lives.

Notle is an innovative AI-powered tool designed to revolutionize mental health practices by transforming how mental health professionals capture and analyze patient interactions in psychotherapy sessions. It utilizes cutting-edge AI models to provide in-depth metrics, predictive analytics, dynamic therapist feedback, interactive therapy exercises, and automated documentation. Notle sets a new benchmark for psychometric evaluation tools with unrivaled precision and reliability, offering advanced behavioral insights and impact in managing personality disorders with groundbreaking precision.

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.

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.

S10.AI is an AI-powered medical scribe application designed to streamline medical documentation processes for healthcare professionals. It offers seamless integration with any EMR system, providing accurate and efficient transcription of patient conversations. The application saves time, ensures confidentiality, and adapts to various medical templates and workflows. S10.AI is praised for its precision, efficiency, and support, making it a valuable asset for practitioners looking to enhance administrative tasks without compromising patient care.

Generate is an experiment to generate data from LLM. It is now deprecated.

Self-Introduction Generate AI is an innovative platform designed to assist individuals and businesses in crafting compelling and effective self-introductions. It leverages advanced AI technology to understand context and generate personalized content. The platform can analyze and understand various types of input, including text and context, to generate tailored self-introductions that are engaging and informative, enhancing personal and professional branding. With features like quick response times, quality assurance, and specialized service for self-introductions, it is an ideal tool for job applications, networking events, and personal branding initiatives.

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.

LangTest is a comprehensive evaluation library for custom LLM and NLP models. It aims to deliver safe and effective language models by providing tools to test model quality, augment training data, and support popular NLP frameworks. LangTest comes with benchmark datasets to challenge and enhance language models, ensuring peak performance in various linguistic tasks. The tool offers more than 60 distinct types of tests with just one line of code, covering aspects like robustness, bias, representation, fairness, and accuracy. It supports testing LLMS for question answering, toxicity, clinical tests, legal support, factuality, sycophancy, and summarization.

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.

LLM-PowerHouse is a comprehensive and curated guide designed to empower developers, researchers, and enthusiasts to harness the true capabilities of Large Language Models (LLMs) and build intelligent applications that push the boundaries of natural language understanding. This GitHub repository provides in-depth articles, codebase mastery, LLM PlayLab, and resources for cost analysis and network visualization. It covers various aspects of LLMs, including NLP, models, training, evaluation metrics, open LLMs, and more. The repository also includes a collection of code examples and tutorials to help users build and deploy LLM-based 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.

The repository 'LLM-for-Healthcare' provides a comprehensive survey of large language models (LLMs) for healthcare, covering data, technology, applications, and accountability and ethics. It includes information on various LLM models, training data, evaluation methods, and computation costs. The repository also discusses tasks such as NER, text classification, question answering, dialogue systems, and generation of medical reports from images in the healthcare domain.

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

This repository provides a curated list of papers, datasets, and resources related to the detection and mitigation of hallucinations in large language models (LLMs). Hallucinations refer to the generation of factually incorrect or nonsensical text by LLMs, which can be a significant challenge for their use in real-world applications. The resources in this repository aim to help researchers and practitioners better understand and address this issue.

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**

TigerBot is a cutting-edge foundation for your very own LLM, providing a world-class large model for innovative Chinese-style contributions. It offers various upgrades and features, such as search mode enhancements, support for large context lengths, and the ability to play text-based games. TigerBot is suitable for prompt-based game engine development, interactive game design, and real-time feedback for playable games.

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.

BAML is a config file format for declaring LLM functions that you can then use in TypeScript or Python. With BAML you can Classify or Extract any structured data using Anthropic, OpenAI or local models (using Ollama) ## Resources  [Discord Community](https://discord.gg/boundaryml)  [Follow us on Twitter](https://twitter.com/boundaryml) * Discord Office Hours - Come ask us anything! We hold office hours most days (9am - 12pm PST). * Documentation - Learn BAML * Documentation - BAML Syntax Reference * Documentation - Prompt engineering tips * Boundary Studio - Observability and more #### Starter projects * BAML + NextJS 14 * BAML + FastAPI + Streaming ## Motivation Calling LLMs in your code is frustrating: * your code uses types everywhere: classes, enums, and arrays * but LLMs speak English, not types BAML makes calling LLMs easy by taking a type-first approach that lives fully in your codebase: 1. Define what your LLM output type is in a .baml file, with rich syntax to describe any field (even enum values) 2. Declare your prompt in the .baml config using those types 3. Add additional LLM config like retries or redundancy 4. Transpile the .baml files to a callable Python or TS function with a type-safe interface. (VSCode extension does this for you automatically). We were inspired by similar patterns for type safety: protobuf and OpenAPI for RPCs, Prisma and SQLAlchemy for databases. BAML guarantees type safety for LLMs and comes with tools to give you a great developer experience:  Jump to BAML code or how Flexible Parsing works without additional LLM calls. | BAML Tooling | Capabilities | | ----------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | BAML Compiler install | Transpiles BAML code to a native Python / Typescript library (you only need it for development, never for releases) Works on Mac, Windows, Linux  | | VSCode Extension install | Syntax highlighting for BAML files Real-time prompt preview Testing UI | | Boundary Studio open (not open source) | Type-safe observability Labeling |

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.

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.

Eyecare Clinical Assistant

Regenerative medicine virtual assistant 'Regen'.

A Medical Research Assistant Chatbot

Explores emerging trends and innovations in medicine.

Especialista em dados de pós-graduação em Fisiologia

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

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)

Engaging, precise assistant for medical professionals.

私と製薬ネタで遊びましょう【注意】私のアウトプットはフィクションです。実在の人物や団体などとは関係ありません。

Rapid, precise medical research expert in orthopaedics.

Generates Angular components based on requirements, with a focus on code-first responses.

Transforms lines into detailed prompts for visual storytelling.

Discover how your writing can shine with a unique and human style. This prompt guides you to create rich and varied texts, surprising with original twists and maintaining coherence and originality. Transform your writing and challenge AI detection tools!

Generate captions for your image and choose the vibe you like.

I generate top 10 PLG strategies in a table format

I generate viral GPT ideas based on your inputs.

Generate your eslint rule

I generate witty trash talk for fantasy football leagues.

Generate dreamy landscapes with silhouette persons

Helps you generate script keyframes, for better experience please visit museclip.ai