Best AI tools for< Improve Healthcare Outcomes >

Medvise is an AI-powered medical scribe and coding engine designed to streamline administrative tasks in the medical field. It offers accurate and efficient medical charting, real-time scribe capabilities, automated data entry, and AI-powered medical coding. The platform ensures compliance with billing guidelines, provides decision support systems for initiating requests verbally, and integrates seamlessly with EHR platforms. Medvise aims to enhance patient care, increase revenue, and improve healthcare outcomes by capturing a wealth of patient information and supporting various healthcare specialties.

The Global Blockchain Show is an annual event that brings together experts and enthusiasts in the blockchain and AI industries. The event features a variety of speakers, workshops, and exhibitions, and provides a platform for attendees to learn about the latest developments in these fields. The 2024 Global Blockchain Show will be held in Dubai, UAE, from April 16-17. The event will feature a keynote address from Sophia, the world's most famous humanoid robot, as well as presentations from other leading experts in the blockchain and AI fields. Attendees will also have the opportunity to network with other professionals in the industry and learn about the latest products and services from leading companies. The Global Blockchain Show is a must-attend event for anyone interested in the latest developments in blockchain and AI.

Kuano is an AI tool that focuses on redefining drug discovery using Quantum and AI technologies. The platform offers world-class scientific expertise in quantum physics, AI, and medicinal chemistry to revolutionize the drug design process. Kuano aims to leverage cutting-edge technologies to accelerate the discovery of new drugs and improve healthcare outcomes.

Youper is an empathetic, safe, and clinically validated AI chatbot designed for mental healthcare. It combines psychology and artificial intelligence to provide support for emotional health issues. Youper has been proven clinically effective at reducing symptoms of anxiety and depression, making mental healthcare accessible to millions of users. The application is used by providers, employers, payers, and life science companies to scale their services and improve mental healthcare outcomes.

Elsevier is an information analytics business that supports researchers and healthcare professionals in advancing science and improving healthcare outcomes. They provide high-quality data and analytics to help researchers, librarians, and research leaders address challenges at every stage of the research journey. Elsevier offers researcher tools, research management solutions, and evaluation services to enhance productivity and research impact.

HEALWELL AI is a healthcare technology company focusing on preventative care through AI and data science. Their mission is to improve healthcare and save lives by early disease detection. HEALWELL provides AI tools for healthcare providers to screen and detect rare, complex, and chronic diseases. They have developed AI clinical co-pilot technologies to assist physicians in early disease detection, ultimately accelerating time to diagnosis and saving lives.

Intelligent Health is the world's leading AI in medicine summit series dedicated to saving lives with AI. The platform hosts a healthtech community committed to advancing pivotal conversations on AI in medicine and fostering global collaboration across the healthcare sector. With a comprehensive agenda offering access to expert voices, Intelligent Health expedites critical discussions on challenges, solutions, and innovations to facilitate key decision-making and impactful investments. The platform aims to ensure the safe, effective, and democratic adoption of AI in healthcare to improve global health outcomes for all.

Limbic is a clinical AI application designed for mental healthcare providers to save time, improve outcomes, and maximize impact. It offers a suite of tools developed by a team of therapists, physicians, and PhDs in computational psychiatry. Limbic is known for its evidence-based approach, safety focus, and commitment to patient care. The application leverages AI technology to enhance various aspects of the mental health pathway, from assessments to therapeutic content delivery. With a strong emphasis on patient safety and clinical accuracy, Limbic aims to support clinicians in meeting the rising demand for mental health services while improving patient outcomes and preventing burnout.

ClosedLoop is a healthcare data science platform that helps organizations improve outcomes and reduce unnecessary costs with accurate, explainable, and actionable predictions of individual-level health risks. The platform provides a comprehensive library of easily modifiable templates for healthcare-specific predictive models, machine learning (ML) features, queries, and data transformation, which accelerates time to value. ClosedLoop's AI/ML platform is designed exclusively for the data science needs of modern healthcare organizations and helps deliver measurable clinical and financial impact.

Ada is a clinically driven AI application that supports better health outcomes and clinical excellence with intelligent technology. It provides users with trusted medical expertise in minutes to understand, manage, and get care for symptoms. Ada also offers powerful enterprise solutions to inform health decisions, enhance triage, and reduce avoidable costs. The application is optimized with human doctors and offers medical guidance in multiple languages, making it a popular choice for symptom assessment and pandemic responses.

ClosedLoop is a healthcare data science platform that helps organizations improve outcomes and reduce costs by providing accurate, explainable, and actionable predictions of individual-level health risks. The platform offers predictive analytics for various healthcare sectors, data science automation, and a healthcare content library to accelerate time to value. ClosedLoop's AI/ML platform is designed exclusively for the data science needs of modern healthcare organizations, enabling proactive interventions, improved clinical outcomes, and innovative healthcare offerings.

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.

Oncora Medical is a healthcare technology company that provides software and data solutions to oncologists and cancer centers. Their products are designed to improve patient care, reduce clinician burnout, and accelerate clinical discoveries. Oncora's flagship product, Oncora Patient Care, is a modern, intelligent user interface for oncologists that simplifies workflow, reduces documentation burden, and optimizes treatment decision making. Oncora Analytics is an adaptive visual and backend software platform for regulatory-grade real world data analytics. Oncora Registry is a platform to capture and report quality data, treatment data, and outcomes data in the oncology space.

Lifestyle Medicine WORKS™ PRO AI is a comprehensive AI-powered platform designed for physicians, healthcare providers, and clinics worldwide. It offers tools and courses to master evidence-based Lifestyle Medicine, reduce team burnout, save time, create new revenue opportunities, and improve chronic diseases patient health outcomes. The platform includes 6 AI Assistants, a 101 Course, business strategies, certification, and more. Lifestyle Medicine WORKS™ PRO AI aims to empower healthcare professionals to seamlessly integrate evidence-based Lifestyle Medicine into their practice and help patients prevent, reduce, and even reverse chronic symptoms.

CloudMedx is a healthcare data platform that provides aggregation, automation, and AI solutions. It simplifies decision making for patients, providers, and payers with a single powerful platform. Clinical, operations, and financial results are coordinated and delivered like never before.

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.

InformAI is a technology company dedicated to advancing healthcare through the development of AI-driven solutions. We focus on crafting high-quality, AI-driven enterprise software solutions that address specific clinical needs. We target critical medical fields including radiology, radiation oncology, and high acuity informatics. Our portfolio, featuring our flagship RadOncAI and our development pipeline products of SinusAI and TransplantAI, is designed to deliver impactful solutions that enhance healthcare quality, safety and efficiency.

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.

PEAR Health Labs is an AI-powered adaptive digital coaching software that offers hyperpersonalized coaching solutions to help individuals move smarter, get healthier, and live happier. The platform utilizes AI technology and physiological science to create personalized fitness experiences based on wearables and biometric feedback. PEAR Training Intelligence aims to change the landscape of preventative care by identifying health issues before they become problems. The software is cost-effective, scalable, and provides guidance on physical activity to improve overall health outcomes.

Seismometer is a suite of tools designed to evaluate AI model performance in healthcare settings. It helps healthcare organizations assess the accuracy of AI models and ensure equitable care for diverse patient populations. The tool allows users to validate model performance using standardized evaluation criteria based on local data and workflows. It includes templates for analyzing statistical performance, fairness across different cohorts, and the impact of interventions on outcomes. Seismometer is continuously evolving to incorporate new validation and analysis techniques.

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, ...

AIDE is a machine learning code generation agent that can generate solutions for machine learning tasks from natural language descriptions. It has the following features: 1. **Instruct with Natural Language**: Describe your problem or additional requirements and expert insights, all in natural language. 2. **Deliver Solution in Source Code**: AIDE will generate Python scripts for the **tested** machine learning pipeline. Enjoy full transparency, reproducibility, and the freedom to further improve the source code! 3. **Iterative Optimization**: AIDE iteratively runs, debugs, evaluates, and improves the ML code, all by itself. 4. **Visualization**: We also provide tools to visualize the solution tree produced by AIDE for a better understanding of its experimentation process. This gives you insights not only about what works but also what doesn't. AIDE has been benchmarked on over 60 Kaggle data science competitions and has demonstrated impressive performance, surpassing 50% of Kaggle participants on average. It is particularly well-suited for tasks that require complex data preprocessing, feature engineering, and model selection.

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**

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.

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.

AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.

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.

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.

This repository is an updating survey for Continual Learning of Large Language Models (CL-LLMs), providing a comprehensive overview of various aspects related to the continual learning of large language models. It covers topics such as continual pre-training, domain-adaptive pre-training, continual fine-tuning, model refinement, model alignment, multimodal LLMs, and miscellaneous aspects. The survey includes a collection of relevant papers, each focusing on different areas within the field of continual learning of large language models.

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.

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.

A collection of papers related to knowledge distillation of large language models (LLMs). The repository focuses on techniques to transfer advanced capabilities from proprietary LLMs to smaller models, compress open-source LLMs, and refine their performance. It covers various aspects of knowledge distillation, including algorithms, skill distillation, verticalization distillation in fields like law, medical & healthcare, finance, science, and miscellaneous domains. The repository provides a comprehensive overview of the research in the area of knowledge distillation of LLMs.

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.

Expert in healthcare data analysis, coding, and clinical trials.

Insights on AI in healthcare and wellness

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Professional advice for healthcare managers

I can help you with healthcare UX design

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Analyzes CME evaluation data for insights.

Efficient planner for nurses with subtle priority management.

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Guide on medical equipment, ailment-based recommendations & image analysis

Expert on marketing to foreign patients in Korea

stunspot's simulation of a Biohacking Expert

Expert data analyst with a focus on diabetes data structure analysis.

Compassionate well-being companion.

AI MCAT tutor with a focus on challenging topics, structured learning, and supportive guidance.

Memory training and cognitive skill enhancer

Your go-to assistant for ICD-11 and related web searches

Specialising in pharmaceutical research, medical science, and biotech

Write Excellent Medical Notes