Best AI tools for< Clinical Talent Acquisition Specialist >

Nolea is an AI-powered healthcare talent discovery platform that revolutionizes healthcare recruiting by leveraging artificial intelligence to find, engage, and hire the best clinical talent faster than ever before. The platform offers features such as AI-powered clinical search, healthcare-specific outreach, clinical talent insights, AI chat assistant, profile evaluation, email outreach, and more. Nolea helps healthcare organizations make data-driven decisions, engage with candidates 24/7, and transform their recruiting process with personalized and efficient workflows.

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.

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.

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.

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.

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.

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.

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.

Neuralink is a pioneering brain-computer interface (BCI) application that aims to redefine human capabilities by creating a generalized brain interface to restore autonomy to individuals with unmet medical needs. The application focuses on developing fully implantable BCIs that allow users, particularly those with quadriplegia, to control computers and mobile devices using their thoughts. Neuralink's innovative technology includes advanced chips, biocompatible enclosures, and surgical robots for precise implantation. The application prioritizes safety, accessibility, and reliability in its engineering process, with future goals of restoring vision, motor function, and speech capabilities.

Wysa is an AI-powered mental health application that provides immediate support through clinically validated AI chat conversations. It offers anonymous and unlimited care to help individuals work through worries, stressors, and symptoms of depression or anxiety. Wysa also provides structured programs, on-demand self-care exercises, and access to professional support for users in need. The application aims to transform how teams and families feel supported by leveraging AI technology to improve mental health outcomes globally.

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.

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.

AiCure provides a patient-centric eClinical trial management platform that enhances drug development through improved medication adherence rates, more powerful analysis and prediction of treatment response using digital biomarkers, and reduced clinical tech burden. AiCure's solutions support traditional, decentralized, or hybrid trials and offer flexibility to meet the needs of various research designs.

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.

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.

RapidAI is a software platform powered by AI that focuses on aneurysm, pulmonary embolism, and stroke. It offers a range of products and solutions designed to improve patient care and efficiency in hospitals. The technology is clinically rooted and revolutionary, developed by clinicians for clinicians. RapidAI's AI-based platform is known for its speed, scalability, and security, with customization options to meet specific hospital needs. The platform has been trusted by 2,200 hospitals, impacting 90 million lives over 15 years of technological development.

NeuProScan is an AI platform designed for the early detection of pre-clinical Alzheimer's from MRI scans. It utilizes AI technology to predict the likelihood of developing Alzheimer's years in advance, helping doctors improve diagnosis accuracy and optimize the use of costly PET scans. The platform is fully customizable, user-friendly, and can be run on devices or in the cloud. NeuProScan aims to provide patients and healthcare systems with valuable insights for better planning and decision-making.

Tempus is an AI-enabled precision medicine company that brings the power of data and artificial intelligence to healthcare. With the power of AI, Tempus accelerates the discovery of novel targets, predicts the effectiveness of treatments, identifies potentially life-saving clinical trials, and diagnoses multiple diseases earlier. Tempus's innovative technology includes ONE, an AI-enabled clinical assistant; NEXT, a tool to identify and close gaps in care; LENS, a platform to find, access, and analyze multimodal real-world data; and ALGOS, algorithmic models connected to Tempus's assays to provide additional insight.

Tempus is an AI-enabled precision medicine company that brings the power of data and artificial intelligence to healthcare. With the power of AI, Tempus accelerates the discovery of novel targets, predicts the effectiveness of treatments, identifies potentially life-saving clinical trials, and diagnoses multiple diseases earlier. Tempus' innovative technology includes ONE, an AI-enabled clinical assistant; NEXT, which identifies and closes gaps in care; LENS, which finds, accesses, and analyzes multimodal real-world data; and ALGOS, algorithmic models connected to Tempus' assays to provide additional insight.

PumasAI is an AI tool designed to accelerate access to life-saving treatments for patients by providing data analytics tools and personalized treatments for drug development and healthcare delivery needs. The company has been recognized for its innovative contributions to the pharmaceutical industry, helping in making data-driven decisions more efficiently. PumasAI aims to save time and money for its clients through its fine-tuned offerings and successful regulatory submissions.

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.

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.

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 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.

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.

ChemicalQDevice innovates new LLM/LLM agent pharmaceutical industry applications regarding cancer drug cost containment, clinical decision support, cancer signaling pathways, bioprocess engineering, biosynthesis, characterization, or drug synthesis. OpenAI, Anthropic, Gemini, or xAI direct chat proprietary software are utilized to generate LLM reports and propose detailed solutions. AI governance is employed with relevant software implementations, model bias amplification mitigation, and generation traceability analyses.

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.

GPT4DFCI is a private and secure generative AI tool based on GPT-4, deployed for non-clinical use at Dana-Farber Cancer Institute. The tool is overseen by the Dana-Farber AI Governance Committee and developed by the Dana-Farber Informatics & Analytics Department. The repository includes manuscript & policy details, training material, front-end and back-end code, infrastructure information, API client for programmatic use, licensing details, and contact information.

Grand Challenge is a platform that provides access to large amounts of annotated training data, objective comparisons of state-of-the-art machine learning solutions, and clinical validation using real-world data. It assists researchers, data scientists, and clinicians in collaborating to develop robust machine learning solutions to problems in biomedical imaging.

Cyclops is a toolkit for facilitating research and deployment of ML models for healthcare. It provides a few high-level APIs namely: data - Create datasets for training, inference and evaluation. We use the popular 🤗 datasets to efficiently load and slice different modalities of data models - Use common model implementations using scikit-learn and PyTorch tasks - Use common ML task formulations such as binary classification or multi-label classification on tabular, time-series and image data evaluate - Evaluate models on clinical prediction tasks monitor - Detect dataset shift relevant for clinical use cases report - Create model report cards for clinical ML models

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.

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.

Kaapana is an open-source toolkit for state-of-the-art platform provisioning in the field of medical data analysis. The applications comprise AI-based workflows and federated learning scenarios with a focus on radiological and radiotherapeutic imaging. Obtaining large amounts of medical data necessary for developing and training modern machine learning methods is an extremely challenging effort that often fails in a multi-center setting, e.g. due to technical, organizational and legal hurdles. A federated approach where the data remains under the authority of the individual institutions and is only processed on-site is, in contrast, a promising approach ideally suited to overcome these difficulties. Following this federated concept, the goal of Kaapana is to provide a framework and a set of tools for sharing data processing algorithms, for standardized workflow design and execution as well as for performing distributed method development. This will facilitate data analysis in a compliant way enabling researchers and clinicians to perform large-scale multi-center studies. By adhering to established standards and by adopting widely used open technologies for private cloud development and containerized data processing, Kaapana integrates seamlessly with the existing clinical IT infrastructure, such as the Picture Archiving and Communication System (PACS), and ensures modularity and easy extensibility.

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.

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.

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.

ToolUniverse is a collection of 211 biomedical tools designed for Agentic AI, providing access to biomedical knowledge for solving therapeutic reasoning tasks. The tools cover various aspects of drugs and diseases, linked to trusted sources like US FDA-approved drugs since 1939, Open Targets, and Monarch Initiative.

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.

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.

As the Pharma Talent Coach, I specialize in career coaching for the pharmaceutical and biotechnology industries. I offer resume analysis and interview coaching. By Glen Osiemo

Comprehensive Guide in Clinical Trials & Regulations

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

I can assist doctors with information synthesis, medical literature reviews, patient education material, diagnostic guidelines, treatment options, ethical dilemmas, and staying updated on medical research and innovations.

Expert AI Doctor with up to date medical resources and textbooks to help improve your clinical skills.

Direct, insightful EEG and neurofeedback analysis specialist.

Accurate and timely matching of patients with clinical trials

Find active recruiting oncology clinical trials near you.

Expert in oncology trial matching, leveraging advanced GPT-4 Turbo techniques.

Explains clinical training at Tokamachi Hospital.

Clinical trial assistant answering questions about clinical trials.

Expert in creating tailored clinical psychology workshop presentations

Formally evaluates clinical cases against CDC/NHSN HAI surveillance definition criteria

Eyecare Clinical Assistant

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)

A therapist blending clinical methods with Eastern and Western philosophies.

Discuss AI and Theory of Mind with Clinical Psychologist Dr. Tamara Russel PHD and AI Expert Cris Ippolite

Expert in biology, always ready to clarify new stem cell treatments.biomedical research, clinical trials. Learn about different stem cell types, current/future uses, and the latest in research.

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)

A guide for Therapists in Person-centered or students in this field, aimed at assisting in patient sessions, providing literature suggestions, and offering reflections on the clinical interventions of users.