Best AI tools for< Enhance Clinical Workflows >

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.

HOPPR is a medical-grade platform that accelerates the development of tailored applications to enhance clinical care and optimize workflows. The platform streamlines AI development in medical imaging, prioritizes data security and privacy, and offers diverse datasets across modalities, anatomies, demographics, and geographies. HOPPR empowers faster prototyping, hypothesis testing, and scalable applications for research and medical imaging services, addressing the growing crisis in medical imaging by enabling partners to rapidly develop solutions that improve patient care, enhance operational efficiency, and increase clinician satisfaction.

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.

Careo AI is an advanced AI-driven solution that is transforming clinical recruitment and revolutionizing healthcare staffing. The platform offers cutting-edge technology to streamline candidate management, vacancy tracking, workflow automation, analytics, and reporting. It provides seamless integration with existing systems, customization, and scalability for recruitment agencies. Careo AI aims to optimize recruitment strategies and enhance productivity in the healthcare industry.

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.

Navina AI is a clinician-first AI platform designed to streamline patient care by providing key insights and actionable recommendations to healthcare providers, ACOs, MSOs, and health plans. The platform leverages proprietary AI technology to improve clinical decision-making, reduce administrative burden, and enhance quality management and risk adjustment processes. Navina AI offers efficient chart review, accurate risk adjustment, streamlined quality management, robust analytics, and a user-friendly interface that integrates seamlessly into the clinical workflow.

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.

BetterMedicine is an AI software designed for cancer diagnostics and detection. It offers AI-powered solutions to enhance patient outcomes and drive efficiency in radiology workflows. The software is expertly designed by medical professionals and AI specialists, providing trusted and clinically validated solutions. BetterMedicine aims to address inefficiencies in radiology by integrating AI-powered software for detecting lesions on CT scans seamlessly into the workflow, thereby improving efficiency and reducing the risk of oversight. The application focuses on improving patient outcomes, reducing errors, and enhancing the wellbeing of radiology professionals.

Glass Health is an AI-powered clinical decision support platform that empowers clinicians by providing tools to develop differential diagnoses and draft clinical plans. The platform combines cutting-edge AI technology with evidence-based medical knowledge to streamline diagnostic decisions and optimize clinician workflows. Glass Health's mission is to leverage technology to enhance the practice of medicine, increase diagnostic accuracy, implement evidence-based medicine, promote health equity, and improve patient outcomes globally. The platform is built by clinicians, for clinicians, with a deep commitment to safety, ethics, and alignment.

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.

Oncora Medical is an AI-powered platform that revolutionizes oncology care management. The platform offers a Clinical Data Platform for automating document generation and enhancing registry informatics. It provides AI-enabled case findings, revenue cycle management solutions, and cancer registry automation. Oncora's comprehensive AI solutions streamline workflows, improve outcomes, and capture revenue through intelligent automation. Trusted by top healthcare organizations worldwide, Oncora empowers healthcare organizations to achieve remarkable results in oncology care.

Bot MD is an AI clinical assistant application that provides instant hospital information search, automates patient monitoring and care, and integrates with a wide range of hospital systems. It is used by thousands of doctors and nurses worldwide to streamline workflows, improve patient care, and enhance communication. The AI chat assistant helps healthcare professionals access clinical information quickly and efficiently, saving time and improving patient outcomes.

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.

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.

iCAD is an AI-powered application designed for cancer detection, specifically focusing on breast cancer. The platform offers a suite of solutions including Detection, Density Assessment, and Risk Evaluation, all backed by science, clinical evidence, and proven patient outcomes. iCAD's AI-powered solutions aim to expose the hiding place of cancer, providing certainty and peace of mind, ultimately improving patient outcomes and saving more lives.

VideaHealth is a dental AI platform trusted by dentists and DSOs. It enhances diagnostics and streamlines workflows using clinical AI to identify and convert treatments across major oral conditions. The platform combines practice management system data with AI insights to elevate patient care and empower dental practices. VideaHealth offers advanced FDA-cleared detection algorithms to detect suspect diseases, provides AI-powered insights for data-driven decisions, and delivers real-time chairside assistance to dentists.

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.

Sully.ai is the #1 all-in-one AI solution designed to save doctors' time by creating superhuman doctors. The platform offers a comprehensive set of features such as pre-visit screening, decision support, scribing, diagnosis assistance, clinical planning, and post-visit automations. Sully.ai is an automation platform that works seamlessly with Electronic Medical Records (EMR) systems, providing personalized and multilingual support for healthcare professionals. The AI model is HIPAA compliant and trained on real-life doctor encounters to enhance decision-making and streamline administrative tasks. With proven results in reducing repetitive tasks and improving efficiency, Sully.ai aims to transform healthcare delivery by empowering doctors to focus on patient care.

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.

Intelligencia AI is a leading provider of AI-powered solutions for the pharmaceutical industry. Our suite of solutions helps de-risk and enhance clinical development and decision-making. We use a combination of data, AI, and machine learning to provide insights into the probability of success for drugs across multiple therapeutic areas. Our solutions are used by many of the top global pharmaceutical companies to improve their R&D productivity and make more informed decisions.

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.

InterpretML is an open-source package that incorporates state-of-the-art machine learning interpretability techniques under one roof. With this package, you can train interpretable glassbox models and explain blackbox systems. InterpretML helps you understand your model's global behavior, or understand the reasons behind individual predictions. Interpretability is essential for: - Model debugging - Why did my model make this mistake? - Feature Engineering - How can I improve my model? - Detecting fairness issues - Does my model discriminate? - Human-AI cooperation - How can I understand and trust the model's decisions? - Regulatory compliance - Does my model satisfy legal requirements? - High-risk applications - Healthcare, finance, judicial, ...

This repository focuses on exploring tools that enhance the performance of language models for various tasks. It provides a structured list of literature relevant to tool-augmented language models, covering topics such as tool basics, tool use paradigm, scenarios, advanced methods, and evaluation. The repository includes papers, preprints, and books that discuss the use of tools in conjunction with language models for tasks like reasoning, question answering, mathematical calculations, accessing knowledge, interacting with the world, and handling non-textual modalities.

MOOSE 2.0 is a leaner, meaner, and stronger tool for 3D medical image segmentation. It is built on the principles of data-centric AI and offers a wide range of segmentation models for both clinical and preclinical settings. MOOSE 2.0 is also versatile, allowing users to use it as a command-line tool for batch processing or as a library package for individual processing in Python projects. With its improved speed, accuracy, and flexibility, MOOSE 2.0 is the go-to tool for segmentation tasks.

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.

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.

This repository contains a collection of papers related to tool learning with large language models (LLMs). The papers are organized according to the survey paper 'Tool Learning with Large Language Models: A Survey'. The survey focuses on the benefits and implementation of tool learning with LLMs, covering aspects such as task planning, tool selection, tool calling, response generation, benchmarks, evaluation, challenges, and future directions in the field. It aims to provide a comprehensive understanding of tool learning with LLMs and inspire further exploration in this emerging area.

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.

Awesome LLM Strawberry is a collection of research papers and blogs related to OpenAI Strawberry(o1) and Reasoning. The repository is continuously updated to track the frontier of LLM Reasoning.

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.

Awesome deep logic is a curated list of papers and resources focusing on integrating symbolic logic into deep neural networks. It includes surveys, tutorials, and research papers that explore the intersection of logic and deep learning. The repository aims to provide valuable insights and knowledge on how logic can be used to enhance reasoning, knowledge regularization, weak supervision, and explainability in neural networks.

AI-IGU is a GitHub repository focused on Artificial Intelligence (AI) concepts, technology, software development, and algorithm improvement for all ages and professions. It emphasizes the importance of future software for future scientists and the increasing need for software developers in the industry. The repository covers various topics related to AI, including machine learning, deep learning, data mining, data science, big data, and more. It provides educational materials, practical examples, and hands-on projects to enhance software development skills and create awareness in the field of AI.

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.

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.

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.

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.

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I assist doctors in simulations, summarizing patient encounters and devising hypothetical treatment plans.

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