Best AI tools for< Enhance Clinical Data >

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.

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.

Puppeteer is an AI application that offers Gen AI Nurses to empower patient support in healthcare. It addresses staffing shortages and enhances access to quality care through personalized and human-like patient experiences. The platform revolutionizes patient intake with features like mental health companions, virtual assistants, streamlined data collection, and clinic customization. Additionally, Puppeteer provides a comprehensive solution for building conversational bots, real-time API and database integrations, and personalized user experiences. It also offers a chatbot service for direct patient interaction and support in psychological help-seeking. The platform is designed to enhance healthcare delivery through AI integration and Large Language Models (LLMs) for modern medical solutions.

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.

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.

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.

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.

Healthray is a Next-Gen AI Hospital Management System that offers a comprehensive suite of healthcare software solutions, including Hospital Information Management System (HIMS), EMR Software, EHR Software, Pharmacy Management System (PMS), and Laboratory Information Management System (LIMS). The platform leverages cutting-edge AI technology to streamline operations, elevate patient care, and optimize administrative efficiency for healthcare providers. Healthray caters to a wide range of medical specialties and offers advanced functionalities to revolutionize traditional healthcare practices. With a focus on digital healthcare solutions and AI integration, Healthray aims to transform the healthcare industry by providing innovative tools for doctors and hospitals.

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.

The Unlearn Platform is an AI-powered platform that streamlines clinical trials by creating digital twins of patients using clinical trial data. It predicts clinical outcomes with unparalleled precision, accelerates timelines, enhances decision-making, and identifies sensitive clinical outcomes. The platform minimizes trial failure, cuts costs, and accelerates approval, ultimately optimizing study endpoints and composite scores.

DrugCard is an AI-enabled Data Intelligence platform designed to streamline drug safety routines by providing continuous and regular, traceable, transparent, accurate, complete, and scalable solutions for pharmacovigilance processes. The platform supports over 100 languages, monitors 1000+ local journals, and saves up to 70% of time compared to manual approaches. DrugCard caters to CROs, MAHs, and freelancers, offering efficient local literature screening services to ensure compliance with regulatory requirements and enhance productivity.

Woebot Health is an AI-driven enterprise solution for mental health that aims to increase access to mental health support and improve business outcomes. It offers in-the-moment mental health support through an app, providing interactive conversations, tools for emotional regulation, mood monitoring, and management. Woebot is not generative AI but rules-based, incorporating elements from Cognitive Behavioral Therapy, Interpersonal Psychotherapy, and Dialectical Behavioral Therapy. The platform also includes data analytics to aggregate insights for clinicians and increase visibility beyond traditional care settings.

Abridge is an enterprise-grade AI platform for clinical conversations, transforming patient-clinician interactions into structured clinical notes in real-time. It is trusted by leading healthcare systems and offers auditable AI infrastructure. The platform aims to improve clinician efficiency, patient care, and overall healthcare outcomes through advanced AI technology.

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.

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.

Astra Health is a leading multilingual AI scribe for clinicians, empowering healthcare providers with a medical notes creation solution that uses generative AI to draft notes, transcribe conversations in real-time, and automate clinical documentation. The application supports 35 languages, offers ambient listening mode, instant notes generation, custom templates creation, and voice-controlled assistant for managing clinical documentation. Astra Health prioritizes ethical and safe practices, ensuring data security and compliance with privacy regulations.

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.

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.

Salt AI is a development engine tailored for life sciences organizations, aiming to accelerate advancements in the field by enabling faster adoption and utilization of AI technologies. The platform offers reliable and reproducible AI processes, optimized for speed and efficiency, and promotes transparency and collaboration within workflows. With a focus on supporting best-in-class life sciences research models, Salt AI empowers users to enhance their understanding of biological processes through flexible and performant AI solutions.

Qventus is an AI-powered platform that simplifies healthcare operations by utilizing AI, machine learning, and behavioral science to automate processes, predict bottlenecks, and optimize care flows. It offers solutions for surgical growth, inpatient capacity management, and perioperative care coordination. Qventus empowers care teams to operate at the top of their license, improve patient outcomes, and enhance operational efficiency in healthcare settings.

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.

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.

SurveyX is an advanced academic survey automation system that leverages Large Language Models (LLMs) to generate high-quality, domain-specific academic papers and surveys. Users can request comprehensive academic papers or surveys tailored to specific topics by providing a paper title and keywords for literature retrieval. The system streamlines academic research by automating paper creation, saving users time and effort in compiling research content.

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.

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.

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.

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.

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.

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-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.

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.

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.

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.

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.

Nmed2024 is a GitHub repository that contains code for a neural network model designed for medical image analysis. The repository includes scripts for training the model, as well as pre-trained weights for quick deployment. The model is specifically tailored for detecting abnormalities in medical images, such as tumors or fractures. It utilizes deep learning techniques to achieve high accuracy and can be easily integrated into existing medical imaging systems. Researchers and developers in the healthcare industry can leverage this tool to enhance the efficiency and accuracy of medical image analysis 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.

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.

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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