Best Healthcare AI Software for Freelancers

Compare the Top Healthcare AI Software for Freelancers as of March 2026

What is Healthcare AI Software for Freelancers?

Healthcare AI software offers a variety of different artificial intelligence applications for healthcare, medicine, research, and more. Healthcare AI software can be used for advanced medical imaging, diagnosing, drug discovery, clinical research, and more. Compare and read user reviews of the best Healthcare AI software for Freelancers currently available using the table below. This list is updated regularly.

  • 1
    BIOiSIM

    BIOiSIM

    VERISIMLife

    BIOiSIMTM is a first-in-class 'virtual drug development engine' that offers unprecedented value for the drug development industry by narrowing down the number of drug compounds that offer anticipated value for the treatment or cure of specific illnesses or diseases. We offer a range of translational-based solutions, customized for your pre-clinical and clinical programs. These offerings are all centered around our proven and validated BIOiSIMTM platform for small molecules, large molecules, and viruses. Our models are built on data from thousands of compounds across 7 species, leading to robustness rarely seen in the industry. With a focus on human outcomes, the platform has at its core a translatability engine that transforms insights across species. The BIOiSIMTM platform can be used before the preclinical animal trial start, allowing earlier insights and savings in expensive outsourced experimentation.
  • 2
    Atomwise

    Atomwise

    Atomwise

    We use our AI engine to transform drug discovery. Our discoveries help create better medicines faster. Our AI-enabled discovery portfolio includes wholly-owned and co-developed pipeline assets, and is backed by prominent investors. Atomwise developed a machine-learning-based discovery engine that combines the power of convolutional neural networks with massive chemical libraries to discover new small-molecule medicines. The secret to reinventing drug discovery with AI is people. We are dedicated to developing the best AI platform and using it to transform small molecule drug discovery. We have to tackle the most challenging, seemingly impossible targets and streamline the drug discovery process to give drug developers more shots on goal. Computational efficiency enables screening of trillions of compounds in silico, increasing the likelihood of success. Demonstrated exquisite model accuracy, overcoming the challenge of false positives.
  • 3
    Recursion

    Recursion

    Recursion

    Recursion is a TechBio company focused on transforming drug discovery by combining biology, data, and artificial intelligence. Founded over a decade ago, the company pioneered the use of large-scale cellular imaging to train AI models that decode the biological drivers of disease. Recursion’s mission is to deliver better medicines through novel insights and precision design, reducing the high failure rates of traditional drug development. Its proprietary Recursion OS platform integrates massive biological datasets with machine learning to accelerate discovery from target identification to clinical development. The company has built an advanced pipeline of potential first-in-class and best-in-class therapies targeting aggressive cancers and rare diseases. Automated wet labs and robotics enable millions of experiments per week, feeding continuous learning into its AI models.
  • 4
    SpliceCore

    SpliceCore

    Envisagenics

    Using RNA sequencing (RNA-seq) data and Artificial Intelligence are both a necessity and an opportunity to develop therapeutics that target splicing errors. The use of machine learning enables us to discover new splicing errors and quickly design therapeutic compounds to correct them. SpliceCore is our dedicated AI platform for RNA therapeutics discovery. We developed this technology platform specifically for the analysis of RNA sequencing data. It can identify, test and validate hypothetical drug targets faster than traditional methods. At the heart of SpliceCore is our proprietary database of more than 5 million potential RNA splicing errors. It is the largest database of splicing errors in the world and it is used to test every RNA sequencing dataset that is input for analysis. Scalable cloud computing enables us to process massive amounts of RNA sequencing data efficiently, at higher speed and lower cost, exponentially accelerating therapeutic innovation.
  • 5
    Genomenon

    Genomenon

    Genomenon

    Pharma companies need comprehensive genomic information to drive successful precision medicine programs, but decisions are often made using only a fraction of the data available, about 10%. Genomenon delivers 100% of the data. An efficient and cost-effective natural history research solution for pharma, ProdigyTM Patient Landscapes support the development of rare disease therapies by enhancing insights contained in retrospective and prospective health data. Using a powerful AI-driven approach, Genomenon delivers a comprehensive and expert assessment of every patient in the published medical literature, in a fraction of the time. Don’t miss anything, get insight into every genomic biomarker published in the medical literature. Every scientific assertion is supported by empirical evidence from the medical literature. Identify all genetic drivers and pinpoint which variants are known to be pathogenic according to ACMG clinical standards.
  • 6
    NVIDIA BioNeMo
    BioNeMo is an AI-powered drug discovery cloud service and framework built on NVIDIA NeMo Megatron for training and deploying large biomolecular transformer AI models at a supercomputing scale. The service includes pre-trained large language models (LLMs) and native support for common file formats for proteins, DNA, RNA, and chemistry, providing data loaders for SMILES for molecular structures and FASTA for amino acid and nucleotide sequences. The BioNeMo framework will also be available for download for running on your own infrastructure. ESM-1, based on Meta AI’s state-of-the-art ESM-1b, and ProtT5 are transformer-based protein language models that can be used to generate learned embeddings for tasks like protein structure and property prediction. OpenFold, a deep learning model for 3D structure prediction of novel protein sequences, will be available in BioNeMo service.
  • 7
    NVIDIA Clara
    Clara’s domain-specific tools, AI pre-trained models, and accelerated applications are enabling AI breakthroughs in numerous fields, including medical devices, imaging, drug discovery, and genomics. Explore the end-to-end pipeline of medical device development and deployment with the Holoscan platform. Build containerized AI apps with the Holoscan SDK and MONAI, and streamline deployment in next-generation AI devices with the NVIDIA IGX developer kits. The NVIDIA Holoscan SDK includes healthcare-specific acceleration libraries, pre-trained AI models, and reference applications for computational medical devices.
  • 8
    AIDDISON

    AIDDISON

    Merck KGaA

    AIDDISON™ drug discovery software combines the power of artificial intelligence (AI), machine learning (ML), and 3D computer-aided drug design (CADD) methods to act as a valuable toolkit for medicinal chemistry needs. As a unified platform for efficient and effective ligand-based and structure-based drug design, it integrates all the facets for virtual screening and supports methods for in-silico lead discovery and lead optimization.
  • 9
    BioSymetrics

    BioSymetrics

    BioSymetrics

    We integrate clinical and experimental data using machine learning to navigate human disease biology and advance precision medicines. Our patent-pending Contingent AI™ understands relationships within the data to provide sophisticated insights. We address data bias by iterating on machine learning models based upon decisions made in the pre-processing and feature engineering stages. We leverage zebrafish, cellular and other phenotypic animal models to validate in silico predictions in vivo experiments and genetically modify them in vitro and in vivo, to improve translation. Using active learning and computer vision on validated models for cardiac, central nervous system and rare disorders, we rapidly incorporate new data into our machine learning models.
  • 10
    Causaly

    Causaly

    Causaly

    Leverage the power of AI to expedite the journey from bench research and laboratory insights to the launch of life-changing therapies. Gain up to 90% in research productivity by reducing your reading time from months to minutes. Cut through the noise with a high-precision, high-accuracy search to navigate the ever-growing volume of scientific literature with ease. Save time, reduce bias and increase odds of novel discoveries. Deeply explore disease biology and conduct advanced target discovery. Causaly’s high-precision knowledge graph consolidates evidence from millions of publications, making deep, unbiased scientific exploration possible. Rapidly navigate biological cause-and-effect relationships without being an expert. Get a view of all scientific documents and uncover hidden connections. Causaly’s powerful AI machine reads millions of published biomedical literature to support better decision-making and research outcomes.
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