Best AI tools for< Code Medical Diagnoses >

Corti is an AI platform that provides advanced capabilities for patient consultations. It offers features such as Co-Pilot, a proactive AI scribe and assistant for clinicians, and Mission Control, an AI-powered conversation recorder. Corti's AI tools support various healthcare tasks, including high precision procedure and diagnosis coding, context-aware assistants for clinicians, and support for multiple languages in speech and text. The platform is trusted by major hospitals and healthcare providers worldwide.

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.

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.

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 capabilities. Suki has deep integrations with major EHR systems, ensuring seamless data flow. The AI is designed to prioritize safety and accuracy, with clinician-reviewed content before integration. Suki provides hassle-free partnerships, proven ROI, and advanced EHR integrations, making it a trusted choice for health systems nationwide.

MediCodio is an AI medical coding assistant that combines automation with medical coders' expertise to streamline the medical coding process. It uses advanced technologies such as AI, ML, RPA, and NLP to suggest relevant codes based on patient charts, improving accuracy and speed within revenue cycle management. The tool enhances efficiency by saving time, minimizing claim denials, increasing revenue, and reducing coder burnout. It also offers expert medical coder verification and intelligent code suggestions for improved accuracy and compliance.

Corti is an AI-powered platform that provides real-time decision support, automates documentation and coding, and improves the productivity of patient encounters. It is used by healthcare professionals to enhance the experience of both healthcare professionals and their patients.

Code to Flowchart is an AI-powered tool that helps users visualize and understand program logic instantly. It allows users to convert code into interactive flowcharts with the help of AI analysis. The tool supports all major programming languages, identifies code paths and logic flows, and offers multiple visualization options like flowcharts, sequence diagrams, and class diagrams. Users can export diagrams in various formats and customize color schemes and themes. Code to Flowchart aims to simplify complex code structures and enhance collaboration among developers.

Code & Pepper is an elite software development company specializing in FinTech and HealthTech. They combine human talent with AI tools to deliver efficient solutions. With a focus on specific technologies like React.js, Node.js, Angular, Ruby on Rails, and React Native, they offer custom software products and dedicated software engineers. Their unique talent identification methodology selects the top 1.6% of candidates for exceptional outcomes. Code & Pepper champions human-AI centaur teams, harmonizing creativity with AI precision for superior results.

Code Snippets AI is an AI-powered code snippets library for teams. It helps developers master their codebase with contextually-rich AI chats, integrated with a secure code snippets library. Developers can build new features, fix bugs, add comments, and understand their codebase with the help of Code Snippets AI. The tool is trusted by the best development teams and helps developers code smarter than ever. With Code Snippets AI, developers can leverage the power of a codebase aware assistant, helping them write clean, performance optimized code. They can also create documentation, refactor, debug and generate code with full codebase context. This helps developers spend more time creating code and less time debugging errors.

The Duino Code Generator is a web application that allows users to generate code for Arduino projects. It provides a convenient platform for creating Arduino code snippets without the need for manual coding. The tool simplifies the process of programming Arduino boards by offering a user-friendly interface and automated code generation based on user inputs. Users can quickly generate code for various Arduino functionalities and projects, making it ideal for both beginners and experienced Arduino enthusiasts.

This tool uses AI to explain any piece of code you don't understand. Simply paste the code in the code editor and press "Explain Code" and AI will output a paragraph explaining what the code is doing.

Code Companion AI is a desktop application powered by OpenAI's ChatGPT, designed to aid by performing a myriad of coding tasks. This application streamlines project management with its chatbot interface that can execute shell commands, generate code, handle database queries and review your existing code. Tasks are as simple as sending a message - you could request creation of a .gitignore file, or deploy an app on AWS, and CodeCompanion.AI does it for you. Simply download CodeCompanion.AI from the website to enjoy all features across various programming languages and platforms.

AI Code Reviewer is a tool that uses artificial intelligence to review code. It can help you find bugs, improve code quality, and enforce coding standards.

Code Language Converter is an AI-powered tool that allows you to convert code from one programming language to another. Simply paste your code snippet into the converter and select the desired output language. The AI will then generate the converted code, which you can download or copy and paste into your project.Code Language Converter is a valuable tool for developers of all levels. It can save you time and effort by automating the code conversion process. Additionally, the converter can help you to learn new programming languages by providing you with a way to see how code is written in different languages.

AI Code Translator is an online tool that allows users to translate code or natural language into multiple programming languages. It is powered by artificial intelligence (AI) and provides intelligent and efficient code translation. With AI Code Translator, developers can save time and effort by quickly converting code between different languages, optimizing their development process.

The Robot Code Generator by Pantheon Robotics is a web application that allows users to generate executable robot code from natural language. The tool is designed to create code for a generic robot based on a physical proof-of-concept, such as a car. Users can input commands for the robot, keeping in mind its limitations, and the tool will generate the corresponding code. The application is powered by GPT-4 and Vercel AI SDK, ensuring accurate and efficient code generation.

No Code Camp is an online learning platform that teaches people how to use artificial intelligence (AI) and no-code tools to automate their work and build applications. The platform offers a live, 5-week cohort-based course that covers the essentials of no-code development, including data architecture, interface design, AI scaling, and no-code automation. The course is designed for people with no prior coding experience and is taught by experienced instructors who have built and scaled digital products using no-code tools.

No Code Camp is an AI tool that offers a live, 5-week cohort-based course to turn strategy and operations people into automation experts with AI and No Code. The platform enables non-technical individuals to build applications, automate workflows, and develop web platforms using graphical interfaces, AI, and tool configuration instead of writing code. No Code Camp democratizes software development, making it accessible to a broader audience, speeding up the development process, and reducing the reliance on specialized software development skills. The course covers essential topics such as Data Architecture, Interface Design, AI Scaling, and No Code Automation, equipping participants with the skills needed to automate business processes and build internal tools.

VBA Code Generator is an AI-powered tool that allows users to generate VBA code quickly and efficiently. By inputting requirements, users can instantly generate complex VBA code using simple text instructions with the help of AI. The tool is designed for both beginners and experienced users, offering a versatile application that can handle various VBA tasks, from Excel automation to Access database management. With a focus on saving time and streamlining workflows, VBA Code Generator simplifies the coding process and provides accurate formulas for users' specific needs.

Papers With Code is an AI tool that provides access to the latest research papers in the field of Machine Learning, along with corresponding code implementations. It offers a platform for researchers and enthusiasts to stay updated on state-of-the-art datasets, methods, and trends in the ML domain. Users can explore a wide range of topics such as language modeling, image generation, virtual try-on, and more through the collection of papers and code available on the website.

This repository serves as an educational resource for pharmaceutical and chemistry students to learn the basics of Deep Learning through a collection of Jupyter Notebooks. The content covers various topics such as Introduction to Jupyter, Python, Cheminformatics & RDKit, Linear Regression, Data Science, Linear Algebra, Neural Networks, PyTorch, Convolutional Neural Networks, Transfer Learning, Recurrent Neural Networks, Autoencoders, Graph Neural Networks, and Summary. The notebooks aim to provide theoretical concepts to understand neural networks through code completion, but instructors are encouraged to supplement with their own lectures. The work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

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.

Swarms provides simple, reliable, and agile tools to create your own Swarm tailored to your specific needs. Currently, Swarms is being used in production by RBC, John Deere, and many AI startups.

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.

LoLLMs WebUI (Lord of Large Language Multimodal Systems: One tool to rule them all) is a user-friendly interface to access and utilize various LLM (Large Language Models) and other AI models for a wide range of tasks. With over 500 AI expert conditionings across diverse domains and more than 2500 fine tuned models over multiple domains, LoLLMs WebUI provides an immediate resource for any problem, from car repair to coding assistance, legal matters, medical diagnosis, entertainment, and more. The easy-to-use UI with light and dark mode options, integration with GitHub repository, support for different personalities, and features like thumb up/down rating, copy, edit, and remove messages, local database storage, search, export, and delete multiple discussions, make LoLLMs WebUI a powerful and versatile tool.

Prompt4ReasoningPapers is a repository dedicated to reasoning with language model prompting. It provides a comprehensive survey of cutting-edge research on reasoning abilities with language models. The repository includes papers, methods, analysis, resources, and tools related to reasoning tasks. It aims to support various real-world applications such as medical diagnosis, negotiation, etc.

This repository contains a comprehensive collection of 63 must-know Large Language Models (LLMs) interview questions. It covers topics such as the architecture of LLMs, transformer models, attention mechanisms, training processes, encoder-decoder frameworks, differences between LLMs and traditional statistical language models, handling context and long-term dependencies, transformers for parallelization, applications of LLMs, sentiment analysis, language translation, conversation AI, chatbots, and more. The readme provides detailed explanations, code examples, and insights into utilizing LLMs for various tasks.

The LLM RAG Workshop repository provides a workshop on using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) to generate and understand text in a human-like manner. It includes instructions on setting up the environment, indexing Zoomcamp FAQ documents, creating a Q&A system, and using OpenAI for generation based on retrieved information. The repository focuses on enhancing language model responses with retrieved information from external sources, such as document databases or search engines, to improve factual accuracy and relevance of generated text.

Lobe Chat is an open-source, modern-design ChatGPT/LLMs UI/Framework. Supports speech-synthesis, multi-modal, and extensible ([function call][docs-functionc-call]) plugin system. One-click **FREE** deployment of your private OpenAI ChatGPT/Claude/Gemini/Groq/Ollama chat application.

TrustLLM is a comprehensive study of trustworthiness in LLMs, including principles for different dimensions of trustworthiness, established benchmark, evaluation, and analysis of trustworthiness for mainstream LLMs, and discussion of open challenges and future directions. Specifically, we first propose a set of principles for trustworthy LLMs that span eight different dimensions. Based on these principles, we further establish a benchmark across six dimensions including truthfulness, safety, fairness, robustness, privacy, and machine ethics. We then present a study evaluating 16 mainstream LLMs in TrustLLM, consisting of over 30 datasets. The document explains how to use the trustllm python package to help you assess the performance of your LLM in trustworthiness more quickly. For more details about TrustLLM, please refer to project website.

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.

Awesome LLM Apps is a curated collection of applications that leverage RAG with OpenAI, Anthropic, Gemini, and open-source models. The repository contains projects such as Local Llama-3 with RAG for chatting with webpages locally, Chat with Gmail for interacting with Gmail using natural language, Chat with Substack Newsletter for conversing with Substack newsletters using GPT-4, Chat with PDF for intelligent conversation based on PDF documents, and Chat with YouTube Videos for engaging with YouTube video content through natural language. Users can clone the repository, navigate to specific project directories, install dependencies, and follow project-specific instructions to set up and run the apps. Contributions are encouraged, and new app ideas or improvements can be submitted via pull requests.

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.

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

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.

MING is an open-sourced Chinese medical consultation model fine-tuned based on medical instructions. The main functions of the model are as follows: Medical Q&A: answering medical questions and analyzing cases. Intelligent consultation: giving diagnosis results and suggestions after multiple rounds of consultation.

AI Hospital is a research repository focusing on the interactive evaluation and collaboration of Large Language Models (LLMs) as intern doctors for clinical diagnosis. The repository includes a simulation module tailored for various medical roles, introduces the Multi-View Medical Evaluation (MVME) Benchmark, provides dialog history documents of LLMs, replication instructions, performance evaluation, and guidance for creating intern doctor agents. The collaborative diagnosis with LLMs emphasizes dispute resolution. The study was authored by Zhihao Fan, Jialong Tang, Wei Chen, Siyuan Wang, Zhongyu Wei, Jun Xie, Fei Huang, and Jingren Zhou.

Claude.vim is a Vim plugin that integrates Claude, an AI pair programmer, into your Vim workflow. It allows you to chat with Claude about what to build or how to debug problems, and Claude offers opinions, proposes modifications, or even writes code. The plugin provides a chat/instruction-centric interface optimized for human collaboration, with killer features like access to chat history and vimdiff interface. It can refactor code, modify or extend selected pieces of code, execute complex tasks by reading documentation, cloning git repositories, and more. Note that it is early alpha software and expected to rapidly evolve.

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.

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

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