Best AI tools for< Analyze Biomedical Images >

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.

IXICO is a precision analytics company specializing in intelligent insights in neuroscience. They offer a range of services for drug development analytics, imaging operations, and post-marketing consultancy. With a focus on technology and innovation, IXICO provides expertise in imaging biomarkers, radiological reads, volumetric MRI, PET & SPECT, and advanced MRI. Their TrialTracker platform and Assessa tool utilize innovation and AI for disease modeling and analysis. IXICO supports biopharmaceutical companies in CNS clinical research with cutting-edge neuroimaging techniques and AI technology.

Mind-Video is an AI tool that focuses on high-quality video reconstruction from brain activity data obtained through fMRI scans. The tool aims to bridge the gap between image and video brain decoding by leveraging masked brain modeling, multimodal contrastive learning, spatiotemporal attention, and co-training with an augmented Stable Diffusion model. It is designed to enhance the generation consistency and accuracy of reconstructing continuous visual experiences from brain activities, ultimately contributing to a deeper understanding of human cognitive processes.

Genie TechBio is the world's first AI bioinformatician, offering an LLM-powered omics analysis software that operates entirely in natural language, eliminating the need for coding. Researchers can effortlessly analyze extensive datasets by engaging in a conversation with Genie, receiving recommendations for analysis pipelines, and obtaining results. The tool aims to accelerate biomedical research and empower scientists with newfound data analysis capabilities.

Bionl is a no-code bioinformatics platform designed to streamline biomedical research for researchers and scientists. It offers a full workspace with features such as bioinformatics pipelines customization, GenAI for data analysis, AI-powered literature search, PDF analysis, and access to public datasets. Bionl aims to automate cloud, file system, data, and workflow management for efficient and precise analyses. The platform caters to Pharma and Biotech companies, academic researchers, and bioinformatics CROs, providing powerful tools for genetic analysis and speeding up research processes.

Ignota Labs is a technology company focused on rescuing failing drugs and bringing new life to abandoned projects, ultimately providing hope to patients. The company utilizes a proprietary AI model, SAFEPATH, which applies deep learning to bioinformatics and cheminformatics datasets to solve drug safety issues. Ignota Labs aims to identify promising drug targets, address safety problems in clinical trials, and accelerate the delivery of therapeutically effective drugs to patients.

neurons.bio is an AI application that offers a unique collection of over 100 AI agents designed for drug development, medicine, and life science research. These agents perform specific tasks efficiently, retrieve data from various sources, and provide insights to accelerate research processes. The platform aims to revolutionize drug discovery and development by integrating cutting-edge LLM technology with domain-specific agents, reducing research costs and time to clinic.

SOMA is a Research Automation Platform that accelerates medical innovation by providing up to 100x speedup through process automation. The platform analyzes medical research articles, extracts important concepts, and identifies causal and associative relationships between them. It organizes this information into a specialized database forming a knowledge graph. Researchers can retrieve causal chains, access specific research articles, and perform tasks like concept analysis, drug repurposing, and target discovery. SOMA enhances literature review efficiency by finding relevant articles based on causal chains and keywords specified by the user. It empowers researchers to focus on their research by saving up to 95% of the time spent on pre-processing documents. The platform offers freemium access with extended functionality for 14 days and advanced features available through subscription.

CEBRA is a machine-learning method that compresses time series data to reveal hidden structures in the variability of the data. It excels in analyzing behavioral and neural data simultaneously, allowing for the decoding of activity from the visual cortex of the mouse brain to reconstruct viewed videos. CEBRA is a novel encoding method that leverages both behavioral and neural data to produce consistent and high-performance latent spaces, enabling the mapping of space, uncovering complex kinematic features, and providing rapid, high-accuracy decoding of natural movies from the visual cortex.

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.

Modality.AI is an AI application that has developed an automated, clinically validated system to assess neurological and psychiatric states both in clinic and remotely. The platform utilizes conversational AI to monitor conditions accurately and consistently, allowing researchers and clinicians to review data in near real-time and monitor treatment response over time. Modality.AI collaborates with world-class AI/Machine Learning experts and leading institutions to provide a HIPAA-compliant system for assessing various indications such as ALS, Parkinson's, depression, autism, Huntington's Disease, schizophrenia, and mild cognitive impairment. The platform enables convenient monitoring at home through streaming and analysis of speech and facial responses, without the need for special software or apps. Modality.AI is accessible on various devices with a browser, webcam, and microphone, offering a new approach to efficient and cost-effective clinical trials.

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.

Elicit is a research tool that uses artificial intelligence to help researchers analyze research papers more efficiently. It can summarize papers, extract data, and synthesize findings, saving researchers time and effort. Elicit is used by over 800,000 researchers worldwide and has been featured in publications such as Nature and Science. It is a powerful tool that can help researchers stay up-to-date on the latest research and make new discoveries.

Plerdy is a comprehensive suite of conversion rate optimization tools that helps businesses track, analyze, and convert their website visitors into buyers. With a range of features including website heatmaps, session replay software, pop-up software, website feedback tools, and more, Plerdy provides businesses with the insights they need to improve their website's usability and conversion rates.

TimeComplexity.ai is an AI tool that helps users analyze the runtime complexity of their code. It works seamlessly across different programming languages without the need for headers, imports, or a main statement. Users can simply input their code and get insights into its performance. However, it is important to note that the results provided by TimeComplexity.ai may not always be accurate, so users are advised to use the tool at their own risk.

CLIP Interrogator is a tool that uses the CLIP (Contrastive Language–Image Pre-training) model to analyze images and generate descriptive text or tags. It effectively bridges the gap between visual content and language by interpreting the contents of images through natural language descriptions. The tool is particularly useful for understanding or replicating the style and content of existing images, as it helps in identifying key elements and suggesting prompts for creating similar imagery.

Surveyed.live is an AI-powered video survey platform that allows businesses to collect feedback and insights from customers through customizable survey templates. The platform offers features such as video surveys, AI touch response, comprehensible dashboard, Chrome extension, actionable insights, integration, predefined library, appealing survey creation, customer experience statistics, and more. Surveyed.live helps businesses enhance customer satisfaction, improve decision-making, and drive business growth by leveraging AI technology for video reviews and surveys. The platform caters to various industries including hospitality, healthcare, education, customer service, delivery services, and more, providing a versatile solution for optimizing customer relationships and improving overall business performance.

DINGR is an AI-powered solution designed to help gamers analyze their performance in League of Legends. The tool uses advanced AI algorithms to provide accurate insights into gameplay, comparing individual performance metrics with friends and popular players. Users can track progress, review profiles, analyze matches, and receive live proofs to enhance their gaming skills. DINGR is currently in development, with a beta version available for limited sign-ups.

Comment Explorer is a free tool that allows users to analyze comments on YouTube videos. Users can gain insights into audience engagement, sentiment, and top subjects of discussion. The tool helps content creators understand the impact of their videos and improve interaction with viewers.

This website is an AI tool that helps senior developers analyze AI tech debt. AI tech debt is the technical debt that accumulates when AI systems are developed and deployed. It can be difficult to identify and quantify AI tech debt, but it can have a significant impact on the performance and reliability of AI systems. This tool uses a variety of techniques to analyze AI tech debt, including static analysis, dynamic analysis, and machine learning. It can help senior developers to identify and quantify AI tech debt, and to develop strategies to reduce it.

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.

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.

The Microsoft Health Intelligence Machine Learning Toolbox is a repository that provides low-level and high-level building blocks for Machine Learning / AI researchers and practitioners. It simplifies and streamlines work on deep learning models for healthcare and life sciences by offering tested components such as data loaders, pre-processing tools, deep learning models, and cloud integration utilities. The repository includes two Python packages, 'hi-ml-azure' for helper functions in AzureML, 'hi-ml' for ML components, and 'hi-ml-cpath' for models and workflows related to histopathology images.

This repository includes papers and blogs about Efficient Transformers, Length Extrapolation, Long Term Memory, Retrieval Augmented Generation(RAG), and Evaluation for Long Context Modeling.

Awesome-LLM-Large-Language-Models-Notes is a repository that provides a comprehensive collection of information on various Large Language Models (LLMs) classified by year, size, and name. It includes details on known LLM models, their papers, implementations, and specific characteristics. The repository also covers LLM models classified by architecture, must-read papers, blog articles, tutorials, and implementations from scratch. It serves as a valuable resource for individuals interested in understanding and working with LLMs in the field of Natural Language Processing (NLP).

This repository contains a comprehensive collection of 63 must-know Large Language Models (LLMs) interview questions. It covers topics such as the architecture of LLMs, transformer models, attention mechanisms, training processes, encoder-decoder frameworks, differences between LLMs and traditional statistical language models, handling context and long-term dependencies, transformers for parallelization, applications of LLMs, sentiment analysis, language translation, conversation AI, chatbots, and more. The readme provides detailed explanations, code examples, and insights into utilizing LLMs for various tasks.

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.

OntoGPT is a Python package for extracting structured information from text using large language models, instruction prompts, and ontology-based grounding. It provides a command line interface and a minimal web app for easy usage. The tool has been evaluated on test data and is used in related projects like TALISMAN for gene set analysis. OntoGPT enables users to extract information from text by specifying relevant terms and provides the extracted objects as output.

This tool is designed to detect and classify Alzheimer's Disease using Deep Learning and Machine Learning algorithms on an early basis, which is further optimized using the Crow Search Algorithm (CSA). Alzheimer's is a fatal disease, and early detection is crucial for patients to predetermine their condition and prevent its progression. By analyzing MRI scanned images using Artificial Intelligence technology, this tool can classify patients who may or may not develop AD in the future. The CSA algorithm, combined with ML algorithms, has proven to be the most effective approach for this purpose.

The 'nlp-llms-resources' repository is a comprehensive resource list for Natural Language Processing (NLP) and Large Language Models (LLMs). It covers a wide range of topics including traditional NLP datasets, data acquisition, libraries for NLP, neural networks, sentiment analysis, optical character recognition, information extraction, semantics, topic modeling, multilingual NLP, domain-specific LLMs, vector databases, ethics, costing, books, courses, surveys, aggregators, newsletters, papers, conferences, and societies. The repository provides valuable information and resources for individuals interested in NLP and LLMs.

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.

Efficient Multimodal Large Language Models: A Survey provides a comprehensive review of efficient and lightweight Multimodal Large Language Models (MLLMs), focusing on model size reduction and cost efficiency for edge computing scenarios. The survey covers the timeline of efficient MLLMs, research on efficient structures and strategies, and applications. It discusses current limitations and future directions in efficient MLLM research.

Efficient Multimodal Large Language Models: A Survey provides a comprehensive review of efficient and lightweight Multimodal Large Language Models (MLLMs), focusing on model size reduction and cost efficiency for edge computing scenarios. The survey covers the timeline of efficient MLLMs, research on efficient structures and strategies, and their applications, while also discussing current limitations and future directions.

This repository is a compilation of excellent ML and DL tutorials created by various individuals and organizations. It covers a wide range of topics, including machine learning fundamentals, deep learning, computer vision, natural language processing, reinforcement learning, and more. The resources are organized into categories, making it easy to find the information you need. Whether you're a beginner or an experienced practitioner, you're sure to find something valuable in this repository.

I assist biological image analysis, including ImageJ macro and Python coding.

An expert in bioengineering, skilled in logical problem-solving

Enhanced with biomedical document knowledge for in-depth blood test analysis.

Your personal biomedical engineer. Create anything related to BME.

A biophysicist assistant offering insights into the physics of living systems.

Find recent research for your area of biological interest.

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Expert in all aspects of spectral flow cytometry.

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Assists with research on neuromuscular responses to passive heating.

AI protein design assistant

A Specialized Biochemistry and Pharmaceutical Research Assistant

Expert in Orthopaedic Bioengineering

In-depth CRISPR research and analysis expert, ensuring comprehensive and step-by-step coverage of topics.

I assist with gene data queries and enable file downloads.

I analyze cognitive biases in scenarios and thoughts, providing neutral, educational insights.

Analyze and reverse engineer images. Receive style descriptions and image re-creation prompts.

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I read and analyze annual reports of companies. Just upload the annual report PDF and start asking me questions!