Best AI tools for< Standardize Medical Imaging Data >
20 - AI tool Sites
Enlitic
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
PMcardio is an AI-powered platform that offers accurate and rapid diagnosis of cardiovascular diseases through ECG interpretation. It provides healthcare professionals with the ability to diagnose various cardiac conditions within seconds, ensuring timely referrals and streamlined workflows. PMcardio leverages AI technology to digitize ECG records, enhance clinical decision-making, and standardize ECG reports, ultimately improving the quality of patient care. The platform is designed to cater to both organizations and individuals, offering a range of features and benefits to revolutionize the field of cardiology.
Claravine
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.
Claid.ai
Claid.ai is an AI product photography suite that offers powerful tools to enhance and edit product images effortlessly. With Claid.ai Brush, users can transform ordinary product photos into flawless, high-quality marketing images in seconds. The application is trusted by over 10,000 businesses to streamline their content creation process and achieve consistency in visual branding. Claid.ai provides features such as background and frame standardization, color correction, face restoration, and background removal, all aimed at improving image quality and boosting conversions. The platform also offers API integration for instant access to editing results and seamless automation of image enhancement tasks.
Responsible AI Licenses (RAIL)
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.
Rafay
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
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
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.
People.ai
People.ai is an AI-powered platform that revolutionizes the way businesses approach revenue generation. By leveraging generative AI and automated activity capture, People.ai provides a holistic solution for account and opportunity management, enabling organizations to create a unified Go-To-Market (GTM) motion. The platform offers data-driven insights to empower sales teams with comprehensive information on accounts and opportunities, leading to better relationships and faster deal closures. People.ai automates manual tasks, inspects account and deal health, and provides prescriptive coaching recommendations, ultimately driving immediate results and scalable revenue growth.
Dubble
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.
Aspect
Aspect is a human-level AI interview notes application designed for modern hiring teams. It records, transcribes, highlights, and summarizes interviews to help recruiters focus on candidates. The platform seamlessly integrates AI into interviews, ensuring important details are not missed. Aspect is perfect for recruiters and teams striving to enhance hiring with data-driven insights while standardizing interviews and reducing bias. It automates the sync of interview notes and summaries to the Applicant Tracking System (ATS), streamlining the hiring process and improving decision-making.
Everbility
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.
Kopyst
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.
404 Error Page
The website is a simple error page indicating that the requested page is not found. It is a standard HTTP response code that informs the user that the server could not find the requested page. The 404 error page is a common occurrence on the internet when a user tries to access a page that no longer exists or has been moved.
Lawformer
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
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
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
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
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
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.
20 - Open Source AI Tools
MONAI
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
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.
awesome-open-data-annotation
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
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.
MedLLMsPracticalGuide
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-LLM-Long-Context-Modeling
This repository includes papers and blogs about Efficient Transformers, Length Extrapolation, Long Term Memory, Retrieval Augmented Generation(RAG), and Evaluation for Long Context Modeling.
llms-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.
cellseg_models.pytorch
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.
nlp-llms-resources
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
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.
moonshot
Moonshot is a simple and modular tool developed by the AI Verify Foundation to evaluate Language Model Models (LLMs) and LLM applications. It brings Benchmarking and Red-Teaming together to assist AI developers, compliance teams, and AI system owners in assessing LLM performance. Moonshot can be accessed through various interfaces including User-friendly Web UI, Interactive Command Line Interface, and seamless integration into MLOps workflows via Library APIs or Web APIs. It offers features like benchmarking LLMs from popular model providers, running relevant tests, creating custom cookbooks and recipes, and automating Red Teaming to identify vulnerabilities in AI systems.
codebase-context-spec
The Codebase Context Specification (CCS) project aims to standardize embedding contextual information within codebases to enhance understanding for both AI and human developers. It introduces a convention similar to `.env` and `.editorconfig` files but focused on documenting code for both AI and humans. By providing structured contextual metadata, collaborative documentation guidelines, and standardized context files, developers can improve code comprehension, collaboration, and development efficiency. The project includes a linter for validating context files and provides guidelines for using the specification with AI assistants. Tooling recommendations suggest creating memory systems, IDE plugins, AI model integrations, and agents for context creation and utilization. Future directions include integration with existing documentation systems, dynamic context generation, and support for explicit context overriding.
PurpleLlama
Purple Llama is an umbrella project that aims to provide tools and evaluations to support responsible development and usage of generative AI models. It encompasses components for cybersecurity and input/output safeguards, with plans to expand in the future. The project emphasizes a collaborative approach, borrowing the concept of purple teaming from cybersecurity, to address potential risks and challenges posed by generative AI. Components within Purple Llama are licensed permissively to foster community collaboration and standardize the development of trust and safety tools for generative AI.
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