Best AI tools for< Standardize Medical Imaging Data >

Enlitic provides healthcare data solutions that leverage artificial intelligence to improve data management, clinical workflows, and create a foundation for real-world evidence medical image databases. Their products, ENDEX and ENCOG, utilize computer vision and natural language processing to standardize, protect, and analyze medical imaging data, enabling healthcare providers to optimize workflows, increase efficiencies, and expand capacity.

PMcardio is an AI-powered ECG interpretation platform that offers accurate diagnosis of cardiovascular diseases within seconds. It provides rapid referral to specialists, detects occlusion myocardial infarction, and identifies reduced left ventricular ejection fraction from 12-lead ECGs. PMcardio enhances clinical decision-making, standardizes ECG reports, and ensures data security. The platform is designed for both individuals and organizations in the healthcare sector, offering seamless coordination and high accuracy in diagnostics.

Claravine is an AI tool that creates shared language and standards for marketing data. It eliminates flawed data, conflict, and the blame game by ensuring data accuracy, improving accountability, and building trust. The platform helps enterprise brands and agencies deliver on the promise of modern marketing by consistently creating and applying data standards. With features like defining standards, applying standards, and connecting standards, Claravine maximizes campaign and technology investments to drive better results. Customers report significant improvements in return on ad spend, data compliance, and time spent on manual data processes. The platform enables global collaboration, automates data flows, and adapts quickly to changing business needs. Trusted by global brands, Claravine provides visibility into campaign performance, data consistency across organizations, and a single source of truth for marketing data.

Responsible AI Licenses (RAIL) is an initiative that empowers developers to restrict the use of their AI technology to prevent irresponsible and harmful applications. They provide licenses with behavioral-use clauses to control specific use-cases and prevent misuse of AI artifacts. The organization aims to standardize RAIL Licenses, develop collaboration tools, and educate developers on responsible AI practices.

Claid.ai is an AI product photography suite designed to help eCommerce businesses enhance their product images quickly and efficiently. The tool offers guided background removal, color correction, and image upscaling features to transform ordinary product photos into high-quality marketing images. With Claid.ai, users can achieve consistency in their product catalog, improve conversions with enhanced images, and save time on editing tasks. The tool is trusted by over 10 million eCommerce images to elevate their visual content and boost online sales.

Rafay is an AI-powered platform that accelerates cloud-native and AI/ML initiatives for enterprises. It provides automation for Kubernetes clusters, cloud cost optimization, and AI workbenches as a service. Rafay enables platform teams to focus on innovation by automating self-service cloud infrastructure workflows.

Cercle is an AI platform that advances healthcare for women by transforming healthcare data into real-time, high-quality insights. The platform caters to women's healthcare providers, payors, and pharma companies, helping them run more efficient businesses and provide personalized care. Cercle's Biomedical Graph unlocks insights at unprecedented speed and accuracy, optimizing patient care and improving outcomes in areas such as assisted reproduction and fertility processes.

Klipy is an AI-powered CRM platform that offers a comprehensive solution for managing all aspects of revenue growth. From automating manual tasks to providing insights through AI analytics, Klipy helps businesses streamline their sales processes and enhance customer relationships. The platform is designed to enrich, log, and organize deal flows, while also offering features like call analytics, playbooks, and pipeline orchestration. Klipy is trusted by various companies and is known for its security measures, ensuring data protection through encryption and anonymization. With a focus on growth operations management, Klipy aims to simplify the sales enablement process and improve customer loyalty.

Dubble is a free tool that helps you create step-by-step guides, tutorials, and onboarding resources for your processes. It uses AI to watch how you work and translate your actions into written instructions and screenshots. This makes it easy to document your processes without having to write anything yourself.

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.

Laudio is an intelligent platform designed to help frontline leaders in health systems streamline their work and prioritize high-impact actions with their teams. By integrating essential workflows and leveraging AI technology, Laudio aims to drive large-scale change by saving time, standardizing best practices, and improving employee engagement and patient experience.

Kopyst is an AI-powered documentation tool that revolutionizes the process of creating engaging video and documents. It helps users streamline workflows, create user manuals, SOPs, and training documents with unmatched accuracy and efficiency. Kopyst offers features like instant documentation, versatile application for various document types, AI-powered intelligence, easy sharing and collaboration, and seamless integration with existing tools. The application empowers users to save time, reduce errors, optimize resources, and enhance productivity in documentation tasks.

Vidya.us is an AI-powered platform designed to enhance student engagement by generating thought-provoking and customized questions for effective collaboration in educational settings. The platform offers an AI question generator to simplify classroom engagement, unlimited question libraries for collaboration, and live classroom parameter measurement. Vidya.us aims to streamline content creation and delivery in schools, colleges, and workplaces through innovative AI technology.

Lawformer is an AI-powered tool designed to simplify the process of handling complex legal documents. It offers an extensive database of attorney-drafted clauses and terms for any contract, along with a learning platform to enhance practical skills in contract drafting. Users can create a personalized library, manage contract knowledge efficiently, and find relevant contract clauses quickly. Lawformer has been serving Silicon Valley startups and the UK's entrepreneurial community since 2009 and 2015, respectively, and is recognized as an international platform for online payments. The platform is trusted by legal professionals and students alike for its comprehensive resources and user-friendly interface.

Ongig is an AI-powered software that focuses on enhancing job postings for consistency, inclusivity, and efficiency. It offers solutions to common problems in job descriptions such as manual workflows, inconsistent postings, and bias. Ongig's features include a centralized job library, AI for talent acquisition, ATS integration, HRIS automation, and job description API. The application helps standardize job ads, improve readability, build a job library, remove gender-coded language, and provide API-driven insights for smarter hiring decisions.

Tabula is a visual data analytics tool that uses AI to help businesses get insights from their data. It is easy to use and can be used by anyone, regardless of their technical expertise. Tabula can be used to access and unify data from a variety of sources, standardize and blend datasets, add custom metrics, build stunning reports, and automate repetitive tasks. Tabula is integrated with a variety of data sources and platforms, making it easy to get started.

AudioShake is a cloud-based audio processing platform that uses artificial intelligence (AI) to separate audio into its component parts, such as vocals, music, and effects. This technology can be used for a variety of applications, including mixing and mastering, localization and captioning, interactive audio, and sync licensing.

Apiversion.dev is an AI-powered API versioning platform that helps developers manage and version their APIs. It provides a range of features to make API versioning easier, including automatic versioning, version deprecation, and version promotion. Apiversion.dev also integrates with popular CI/CD tools to automate the API versioning process.

The Princeton Review is an AI-based test preparation and tutoring platform offering personalized academic support, test prep courses, and college admissions counseling. With over 43 years of industry experience and a track record of helping millions of students, The Princeton Review uses sophisticated AI technology to provide students with tailored learning experiences, expert-led videos, interactive reports, and feedback tools for essays and homework. The platform covers a wide range of subjects and exams, from K-12 academics to graduate and professional tests like SAT, ACT, MCAT, LSAT, GRE, GMAT, and more. Additionally, it offers services for college admissions counseling, school partnerships, and international licensing.

ReadTheory is a free online reading comprehension practice tool for students and teachers. It offers personalized reading comprehension exercises for grades K-12 and ESL students, with adaptive technology that adjusts to each student's specific reading level. ReadTheory also provides teachers with easy-to-use reporting and thousands of interactive exercises and worksheets. With ReadTheory, teachers can save time with automatic marking, track individual student and class progress in real-time, and motivate students to read with engaging class competitions, badges, and prizes.

MONAI is a PyTorch-based, open-source framework for deep learning in healthcare imaging. It provides a comprehensive set of tools for medical image analysis, including data preprocessing, model training, and evaluation. MONAI is designed to be flexible and easy to use, making it a valuable resource for researchers and developers in the field of medical imaging.

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.

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.

Supervisely is a computer vision platform that provides a range of tools and services for developing and deploying computer vision solutions. It includes a data labeling platform, a model training platform, and a marketplace for computer vision apps. Supervisely is used by a variety of organizations, including Fortune 500 companies, research institutions, and government agencies.

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.

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

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.

This repository serves as a comprehensive survey on the application of Large Language Models (LLMs) on tabular data, focusing on tasks such as prediction, data generation, and table understanding. It aims to consolidate recent progress in this field by summarizing key techniques, metrics, datasets, models, and optimization approaches. The survey identifies strengths, limitations, unexplored territories, and gaps in the existing literature, providing insights for future research directions. It also offers code and dataset references to empower readers with the necessary tools and knowledge to address challenges in this rapidly evolving domain.

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.

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.

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.

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.

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