Best AI tools for< Cancer Researcher >

The National Cancer Institute's Center for Biomedical Informatics and Information Technology (CBIIT) provides a comprehensive suite of tools, resources, and training to support cancer data science research. These resources include data repositories, analytical tools, data standards, and training materials. CBIIT also develops and maintains the NCI Thesaurus, a comprehensive vocabulary of cancer-related terms, and the Cancer Data Standards Registry and Repository (caDSR), a repository of cancer data standards. CBIIT's mission is to accelerate the pace of cancer research by providing researchers with the tools and resources they need to access, analyze, and share cancer data.

Galleri is a multi-cancer early detection test that uses a single blood draw to screen for over 50 types of cancer. It is recommended for adults aged 50 or older who are at an elevated risk for cancer. Galleri is not a diagnostic test and does not detect all cancers. A positive result requires confirmatory diagnostic evaluation by medically established procedures (e.g., imaging) to confirm cancer.

Lunit Inc. is a leading provider of AI-powered cancer screening and treatment solutions. The company's mission is to conquer cancer through AI by developing innovative technologies that can help detect and treat cancer earlier and more effectively. Lunit's AI solutions are used by hospitals and clinics around the world to improve the accuracy and efficiency of cancer diagnosis and treatment.

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.

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.

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.

Nucleai is an AI-driven spatial biomarker analysis tool that leverages military intelligence-grade geospatial AI methods to analyze complex cellular interactions in a patient's biopsy. The platform offers a first-of-its-kind multimodal solution by ingesting images from various modalities and delivering actionable insights to optimize biomarker scoring, predict response to therapy, and revolutionize disease diagnosis and treatment.

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.

Skinive is an AI-powered dermatology app that provides users with a personalized skin analysis and treatment plan. The app uses a combination of computer vision and machine learning to identify and track skin conditions, such as acne, rosacea, and skin cancer. Skinive also offers a variety of features to help users improve their skin health, such as a personalized skincare routine, a skin diary, and access to a team of dermatologists. Skinive is available as a mobile app and a web app.

ScienceCast is a platform that enhances scientific papers with interactive media, providing a unique way to explore and engage with research articles in various fields such as Biology, Computer Science, Economics, Electrical Engineering, Mathematics, Physics, and more. Users can access a wide range of featured casts, including topics like cancer biology, genomics, immunology, microbiology, molecular biology, biochemistry, and bioinformatics. The platform aims to make complex scientific information more accessible and engaging for researchers and enthusiasts alike.

JADBio is an automated machine learning (AutoML) platform designed to accelerate biomarker discovery and drug development processes. It offers a no-code solution that automates the discovery of biomarkers and interprets their role based on research needs. JADBio can parse multi-omics data, including genomics, transcriptome, metagenome, proteome, metabolome, phenotype/clinical data, and images, enabling users to efficiently discover valuable insights. The platform is purpose-built for various conditions such as cancer, immune, endocrine, metabolic system, chronic diseases, aging, infectious diseases, and mental health, offering solutions for early biomarker discovery, drug repurposing, lead identification, compound optimization, trial monitoring, and response to treatment. JADBio is trusted by partners in precision health & medicine and is continuously evolving to disrupt drug discovery times and costs at all stages.

UXSquid is a comprehensive UX research software platform and tool that guides users through the user research process with interview question examples, plans, templates, and a cheat sheet. It offers a free trial, requires no credit card, and allows users to cancel anytime. UXSquid's platform makes it easy to conduct user interviews and gather feedback. Users can use its automation tools to set up interviews with their target audience and gather valuable information. UXSquid analyzes user experiences and interactions with a company using cutting-edge artificial intelligence. It then makes important suggestions and enhancements to improve a product for its users.

Freenome is a healthcare company that uses artificial intelligence and multiomics technology to detect cancer in its earliest stages through a simple blood draw. The company's mission is to make early cancer detection more accessible and affordable, and to improve the chances of successful treatment.

Freenome is a healthcare company that uses artificial intelligence and multiomics technology to detect cancer in its earliest stages through a simple blood draw. The company's mission is to make early cancer detection more accessible and affordable, and to improve the chances of successful treatment.

Oatmeal Health is an AI-enabled cancer screening application that aims to empower health equality by providing early detection services to underserved Medicare/Medicaid FQHC populations. The application combines primary care support, radiology risk assessments, and advanced therapeutic/clinical trial access for early diagnosis. Oatmeal Health partners with local providers to eliminate cancer care disparities and enhance patient outcomes through innovative technology and clinical solutions.

GRAIL is a healthcare company innovating to solve medicine’s most important challenges. Our team of leading scientists, engineers and clinicians are on an urgent mission to detect cancer early, when it is more treatable and potentially curable. GRAIL's Galleri® test is a first-of-its-kind multi-cancer early detection (MCED) test that can detect a signal shared by more than 50 cancer types and predict the tissue type or organ associated with the signal to help healthcare providers determine next steps.

Proscia is a leading provider of digital pathology solutions for the modern laboratory. Its flagship product, Concentriq, is an enterprise pathology platform that enables anatomic pathology laboratories to achieve 100% digitization and deliver faster, more precise results. Proscia also offers a range of AI applications that can be used to automate tasks, improve diagnostic accuracy, and accelerate research. The company's mission is to perfect cancer diagnosis with intelligent software that changes the way the world practices pathology.

AskEllyn.ai is an AI-powered platform designed to provide support, information, and engagement for individuals and families navigating the challenging journey of breast cancer. The platform offers a range of resources, including chat support, blog articles, and partner recommendations, to help users cope with the emotional and practical aspects of dealing with breast cancer. AskEllyn.ai aims to be a comforting companion and a source of valuable insights for those affected by breast cancer.

Accuray Incorporated is a radiation oncology company that develops, manufactures, and sells radiation therapy systems and software for the treatment of cancer. Accuray's products are used by radiation oncologists to deliver precise and effective radiation therapy treatments to patients with a variety of cancers, including prostate cancer, breast cancer, lung cancer, and brain cancer. Accuray's mission is to expand the curative power of radiation therapy to improve as many lives as possible.

Slideflow is a deep learning library for digital pathology, offering a user-friendly interface for model development. It is designed for medical researchers and AI enthusiasts, providing an accessible platform for developing state-of-the-art pathology models. Slideflow offers customizable training pipelines, robust slide processing and stain normalization toolkit, support for weakly-supervised or strongly-supervised labels, built-in foundation models, multiple-instance learning, self-supervised learning, generative adversarial networks, explainability tools, layer activation analysis tools, uncertainty quantification, interactive user interface for model deployment, and more. It supports both PyTorch and Tensorflow, with optional support for Libvips for slide reading. Slideflow can be installed via pip, Docker container, or from source, and includes non-commercial add-ons for additional tools and pretrained models. It allows users to create projects, extract tiles from slides, train models, and provides evaluation tools like heatmaps and mosaic maps.

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.

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.

ChatGPT is a large language model that can generate human-like text, translate languages, write different kinds of creative content, and answer your questions in a conversational way. It is trained on a massive amount of text data, and it is able to understand and respond to a wide range of natural language prompts. Here are 5 jobs suitable for this tool, in lowercase letters: 1. content writer 2. chatbot assistant 3. language translator 4. creative writer 5. researcher

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.

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.

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.

cellseg-models.pytorch is a Python library built upon PyTorch for 2D cell/nuclei instance segmentation models. It provides multi-task encoder-decoder architectures and post-processing methods for segmenting cell/nuclei instances. The library offers high-level API to define segmentation models, open-source datasets for training, flexibility to modify model components, sliding window inference, multi-GPU inference, benchmarking utilities, regularization techniques, and example notebooks for training and finetuning models with different backbones.

This repository contains advanced LLM-based chatbots for Retrieval Augmented Generation (RAG) and Q&A with different databases. It provides guides on using AzureOpenAI and OpenAI API for each project. The projects include Q&A and RAG with SQL and Tabular Data, and KnowledgeGraph Q&A and RAG with Tabular Data. Key notes emphasize the importance of good column names, read-only database access, and familiarity with query languages. The chatbots allow users to interact with SQL databases, CSV, XLSX files, and graph databases using natural language.

FuseMedML is a Python framework designed to accelerate machine learning-based discovery in the medical field by promoting code reuse. It provides a flexible design concept where data is stored in a nested dictionary, allowing easy handling of multi-modality information. The framework includes components for creating custom models, loss functions, metrics, and data processing operators. Additionally, FuseMedML offers 'batteries included' key components such as fuse.data for data processing, fuse.eval for model evaluation, and fuse.dl for reusable deep learning components. It supports PyTorch and PyTorch Lightning libraries and encourages the creation of domain extensions for specific medical domains.

Weights & Biases (W&B) is a platform that helps users build better machine learning models faster by tracking and visualizing all components of the machine learning pipeline, from datasets to production models. It offers tools for tracking, debugging, evaluating, and monitoring machine learning applications. W&B provides integrations with popular frameworks like PyTorch, TensorFlow/Keras, Hugging Face Transformers, PyTorch Lightning, XGBoost, and Sci-Kit Learn. Users can easily log metrics, visualize performance, and compare experiments using W&B. The platform also supports hosting options in the cloud or on private infrastructure, making it versatile for various deployment needs.

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.

At ZenML, we believe in the importance of annotation and labeling workflows in the machine learning lifecycle. This repository showcases a curated list of open-source data annotation and labeling tools that are actively maintained and fit for purpose. The tools cover various domains such as multi-modal, text, images, audio, video, time series, and other data types. Users can contribute to the list and discover tools for tasks like named entity recognition, data annotation for machine learning, image and video annotation, text classification, sequence labeling, object detection, and more. The repository aims to help users enhance their data-centric workflows by leveraging these tools.

The 'llms-tools' repository is a comprehensive collection of AI tools, open-source projects, and research related to Large Language Models (LLMs) and Chatbots. It covers a wide range of topics such as AI in various domains, open-source models, chats & assistants, visual language models, evaluation tools, libraries, devices, income models, text-to-image, computer vision, audio & speech, code & math, games, robotics, typography, bio & med, military, climate, finance, and presentation. The repository provides valuable resources for researchers, developers, and enthusiasts interested in exploring the capabilities of LLMs and related technologies.

The 'awesome-sound_event_detection' repository is a curated reading list focusing on sound event detection and Sound AI. It includes research papers covering various sub-areas such as learning formulation, network architecture, pooling functions, missing or noisy audio, data augmentation, representation learning, multi-task learning, few-shot learning, zero-shot learning, knowledge transfer, polyphonic sound event detection, loss functions, audio and visual tasks, audio captioning, audio retrieval, audio generation, and more. The repository provides a comprehensive collection of papers, datasets, and resources related to sound event detection and Sound AI, making it a valuable reference for researchers and practitioners in the field.

noScribe is an AI-based software designed for automated audio transcription, specifically tailored for transcribing interviews for qualitative social research or journalistic purposes. It is a free and open-source tool that runs locally on the user's computer, ensuring data privacy. The software can differentiate between speakers and supports transcription in 99 languages. It includes a user-friendly editor for reviewing and correcting transcripts. Developed by Kai Dröge, a PhD in sociology with a background in computer science, noScribe aims to streamline the transcription process and enhance the efficiency of qualitative analysis.

Expert in cancer biology

Medical expert on endometrial cancer, providing detailed and informative responses.

Provides medically-informed insights on breast cancer.

Compassionate support and information on cancer care.

Eradicate Cervical Cancer by Providing Trustworthy Information on HPV

Medical and informative guide on liver cancer.

A medically informative guide on bladder cancer.

Provides information on digestive health and stomach issues, in an informative tone.

Informative guide on lymphoma, covering classification and treatments.

Medical expert on melanoma, informative and detailed.

Expert in SCLC research, focused on a specific paper and broader SCLC knowledge.

Optimistic AI offering hopeful guidance on astrocytomas.

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

Find active recruiting oncology clinical trials near you.

Provides information on thyroid cancer.

Expert in PET/CT imaging, focusing on oncology, cardiology, neurology

Expert on radiation science and its medical applications

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