Best AI tools for< Research Cancer Biology >

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.

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.

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.

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.

Paige is a leading AI company revolutionizing pathology with next-generation technology. They provide diagnostic and biomarker AI, predictive analytics technology, and AI-assisted applications to support cancer detection, subtyping, and molecular biomarker discovery from tissue samples. Paige offers a range of AI suites for prostate, breast, colon, and PanCancer, as well as the innovative Paige Alba™ multi-modal co-pilot. Their advanced AI technology and services help streamline AI development, optimize existing applications, and drive groundbreaking advancements in cancer care.

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 insights for various conditions such as cancer, immune system disorders, chronic diseases, infectious diseases, and mental health. The platform is trusted by partners in precision health and medicine and is continuously evolving to disrupt drug discovery times and costs at all stages.

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.

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.

Google Research is a leading research organization focusing on advancing science and artificial intelligence. They conduct research in various domains such as AI/ML foundations, responsible human-centric technology, science & societal impact, computing paradigms, and algorithms & optimization. Google Research aims to create an environment for diverse research across different time scales and levels of risk, driving advancements in computer science through fundamental and applied research. They publish hundreds of research papers annually, collaborate with the academic community, and work on projects that impact technology used by billions of people worldwide.

Google Research is a team of scientists and engineers working on a wide range of topics in computer science, including artificial intelligence, machine learning, and quantum computing. Our mission is to advance the state of the art in these fields and to develop new technologies that can benefit society. We publish hundreds of research papers each year and collaborate with researchers from around the world. Our work has led to the development of many new products and services, including Google Search, Google Translate, and Google Maps.

The Google Research Blog is a platform for researchers at Google to share their latest work in artificial intelligence, machine learning, and other related fields. The blog covers a wide range of topics, from theoretical research to practical applications. The goal of the blog is to provide a forum for researchers to share their ideas and findings, and to foster collaboration between researchers at Google and around the world.

The Research Center Trustworthy Data Science and Security is a hub for interdisciplinary research focusing on building trust in artificial intelligence, machine learning, and cyber security. The center aims to develop trustworthy intelligent systems through research in trustworthy data analytics, explainable machine learning, and privacy-aware algorithms. By addressing the intersection of technological progress and social acceptance, the center seeks to enable private citizens to understand and trust technology in safety-critical applications.

Research Studio is a next-level UX research tool that helps you streamline your user research with AI-enhanced analysis. Whether you're a freelance UX designer, user researcher, or agency, Research Studio can help you get the insights you need to make better decisions about your products and services.

RapidAI Research Institute is an academic institution under the RapidAI open-source organization, a non-enterprise academic institution. It serves as a platform for academic research and collaboration, providing opportunities for aspiring researchers to publish papers and engage in scholarly activities. The institute offers mentorship programs and benefits for members, including access to resources such as internet connectivity, GPU configurations, and storage space. The management team consists of esteemed professionals in the field, ensuring a conducive environment for academic growth and development.

MIRI (Machine Intelligence Research Institute) is a non-profit research organization dedicated to ensuring that artificial intelligence has a positive impact on humanity. MIRI conducts foundational mathematical research on topics such as decision theory, game theory, and reinforcement learning, with the goal of developing new insights into how to build safe and beneficial AI systems.

Branded Research, acquired by Dynata, provides access to AI-verified audience insights. It offers a range of research methods, including surveys, webcam studies, and emotional AI. With its advanced algorithms and extensive profiling, Branded helps businesses connect with their target audience and gain valuable insights to drive innovation. The company serves various industries, including tech, consumer goods, healthcare, and research agencies.

The Berkeley Artificial Intelligence Research (BAIR) Lab is a renowned research lab at UC Berkeley focusing on computer vision, machine learning, natural language processing, planning, control, and robotics. With over 50 faculty members and 300 graduate students, BAIR conducts research on fundamental advances in AI and interdisciplinary themes like multi-modal deep learning and human-compatible AI.

AIM Research is a leading platform providing insights and analysis on the Artificial Intelligence industry. The website offers a comprehensive range of resources, including research reports, event coverage, news articles, and expert opinions. AIM Research focuses on highlighting the latest trends, innovations, and key players in the AI sector, catering to professionals, researchers, and enthusiasts seeking in-depth knowledge and understanding of AI technologies and applications.

Opus Research is a leading provider of market research, consulting, and advisory services to the global digital communications and collaboration sectors. The company's research focuses on the convergence of emerging technologies, including artificial intelligence (AI), machine learning (ML), and natural language processing (NLP), with the communications and collaboration industries.

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.

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.

Text2Text is a comprehensive language modeling toolkit that offers a wide range of functionalities for text processing and generation. It provides tools for tokenization, embedding, TF-IDF calculations, BM25 scoring, indexing, translation, data augmentation, distance measurement, training/finetuning models, language identification, and serving models via a web server. The toolkit is designed to be user-friendly and efficient, offering a variety of features for natural language processing tasks.

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.

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.

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.

SpeciesNet is an ensemble of AI models designed for classifying wildlife in camera trap images. It consists of an object detector that finds objects of interest in wildlife camera images and an image classifier that classifies those objects to the species level. The ensemble combines these two models using heuristics and geographic information to assign each image to a single category. The models have been trained on a large dataset of camera trap images and are used for species recognition in the Wildlife Insights platform.

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.

Arno's Iptables Firewall (AIF) is a single- & multi-homed firewall script with DSL/ADSL support. It is a free software distributed under the GNU GPL License. The script provides a comprehensive set of configuration files and plugins for setting up and managing firewall rules, including support for NAT, load balancing, and multirouting. It offers detailed instructions for installation and configuration, emphasizing security best practices and caution when modifying settings. The script is designed to protect against hostile attacks by blocking all incoming traffic by default and allowing users to configure specific rules for open ports and network interfaces.

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.

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.

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, ...

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.

The 'ShitSpotter' repository is dedicated to developing a poop-detection algorithm and dataset for creating a phone app that helps locate dog poop in outdoor environments. The project involves training a PyTorch network to detect poop in images and provides scripts for detecting poop in unseen images using a pretrained model. The dataset consists of mostly outdoor images taken with a phone, with a process involving before and after pictures of the poop. The project aims to enable various applications, such as AR glasses for poop detection and efficient cleaning of public areas by city governments. The code, dataset, and pretrained models are open source with permissive licensing and distributed via IPFS, BitTorrent, and centralized mechanisms.

Expert in cancer biology

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

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

Find active recruiting oncology clinical trials near you.

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

Informative guide on lymphoma, covering classification and treatments.

General Information Gatherer

Explains Arxiv papers with examples, analogies, and direct PDF links.

Your AI research aide for the latest in ML.

I improve marketing effectiveness by designing stunning research-led assets in a flash!

Your go-to source for well-researched information!

Spot emerging trends in the latest social science research ( (also see, just "Research Radar" for all disciplines))

Teaches and analyzes research methods with in-depth, academic insights.

Expert AI research question assistant.

Faster, smarter scientific advancement.

Designed to Provide Comprehensive Insights from the AI industry from Reputable Sources.

Expert in crafting high-standard research papers.

Research Proposal Assistant Pro is designed to provide tailored assistance in research writing.

Upon uploading a research paper, I provide a concise section wise analysis covering Abstract, Lit Review, Findings, Methodology, and Conclusion. I also critique the work, highlight its strengths, and answer any open questions from my Knowledge base of Open source materials.

Expert in detailed, interactive, and multilingual research analysis.