Artificial intelligence (AI) is revolutionizing the way healthcare professionals diagnose, treat, and manage diseases. AI-powered medical tools and devices are being used to improve patient outcomes, reduce healthcare costs, and increase efficiency. Here are a few articles that explore how AI is being used in the health and medical fields.
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Aetna’s Next Best Action
Aetna’s Next Best Action is a healthcare strategy aimed at providing personalized guidance and recommendations to individuals based on their unique health needs and goals. The approach includes health coaching, personalized health plans, and access to resources to help individuals make informed decisions about their health. The ultimate goal is to improve health outcomes and reduce healthcare costs. AI algorithms can analyze data from various sources, such as wearable devices and electronic health records, to identify patterns and trends in a patient’s health and behavior and provide personalized recommendations and care plans. The result is real-time and allows individuals to make informed decisions about their health.
Akoya Biosciences x PathAI
Akoya Biosciences and PathAI have partnered to improve immunotherapy treatments for cancer using PathAI’s AI-powered technology. This partnership will support Akoya’s research efforts and help improve cancer diagnosis and treatment accuracy and efficiency. The use of AI is expected to provide valuable insights and accelerate the development of new therapies for better patient outcomes.
Athenahealth x Nuance: athenaOne
Athenahealth partnered with Nuance to release a new AI-powered EHR solution called athenaOne Voice Assistant Powered by Nuance, which is designed to help healthcare providers streamline information retrieval and complete clinical tasks hands-free using voice commands. The goal of athenaOne AI is to save time for healthcare providers and improve the patient experience by allowing for more natural and accurate documentation.
CVS Health x Microsoft
CVS Health uses machine learning on Microsoft Azure Databricks platform to personalize customer and patient experiences by delivering millions of offers to over 80 million customers daily. This effort, started in 2018, helps CVS comply with patient privacy policies while providing a more data-driven and customized experience. The use of Microsoft technology enables CVS to enhance its omnichannel pharmacy capabilities and provide personalized health recommendations. Additionally, CVS plans to scale up retail loyalty and personalization programs using advanced machine learning models on Azure.
Hadassah Medical x Ascento Medical
Hadassah Medical and Ascento Medical have partnered to address neurological degenerative diseases, focusing on dementia. Ascento Medical is utilizing Artificial Intelligence and Machine Learning to optimize a successful treatment procedure, offering hope in the treatment and prevention of dementia and Alzheimer’s disease.
HCA Healthcare x Google Cloud
HCA Healthcare is utilizing Google Cloud’s services to store and analyze patient data and aims to enhance HCA Healthcare’s research capabilities by leveraging Google’s data analytics and machine learning tool. This will enable HCA Healthcare to develop and implement new treatments and procedures more quickly, leading to better patient outcomes.
Pfizer x Atomwise
Atomwise’s AI technology analyzes a vast chemical space to identify potential small molecules that could bind to proteins with high affinity, which can lead to the discovery of new therapeutic opportunities. The technology enables the virtual screening of chemical libraries and can potentially compress the drug discovery process from years to weeks or months.
Pfizer x AWS
The partnership is aimed at accelerating Pfizer’s drug discovery. AWS’s machine learning and artificial intelligence capabilities to identify new drug candidates and accelerate the development of innovative treatments. By leveraging AWS’s cloud computing and AI tools, Pfizer can quickly analyze vast amounts of data to identify new drug targets and accelerate the development of new therapies. AI algorithms can help identify patterns in clinical data that may not be immediately visible to the human eye, making it possible to develop more personalized treatment plans.
Pfizer x Catalia Health
Catalia Health and Pfizer have announced a collaboration to enhance patient care and improve health outcomes. Catalia Health’s conversational AI platform, Mabu, provides personalized support to patients taking Pfizer medications. Mabu will use AI to interact with patients, understand their needs and provide relevant information and guidance on their medication.
Pfizer x CytoReason
CytoReason’s platform utilizes real-world data from pharmaceutical partners to create tissue- and cell-specific models that mimic individual diseases. These models are then analyzed using the company’s machine learning AI, which helps to identify differences between patient groups and treatments. Pfizer hopes to understand the immune system better and develop innovative drugs for immune-mediated and immuno-oncology diseases. CytoReason’s technology has provided Pfizer with multiple insights into its research and development programs across more than 20 diseases.
Pfizer’s Novel Prediction Model
Pfizer developed a novel prediction model using machine learning techniques. The model is designed to identify heart failure patients at risk of developing Wild-Type Transthyretin Amyloid Cardiomyopathy (WT-TTR), a rare and life-threatening condition. The model has demonstrated robust performance in accurately predicting the risk of WT-TTR, making it a valuable tool for healthcare providers in the early detection and management of this condition.
Pfizer x XtalPi
Pfizer formed a partnership with XtalPi, AI-powered technology that helps to optimize the design and development of small-molecule drugs. XtalPi’s AI platform uses deep learning algorithms and big data analysis to simulate and optimize the crystal structures of drug molecules. This helps drug developers to identify the most promising compounds for further development and accelerate the drug discovery process.
Siemens Healthineers x Enlitic Freenome
Enlitic Freenome will provide its AI-powered image analysis technology to support Siemens Healthineers’ efforts to develop innovative cancer diagnosis and treatment solutions. The use of AI is expected to help healthcare providers make more informed decisions and improve patient outcomes by enabling earlier and more accurate diagnoses.
Stanford Medicine x Komodo
Stanford Medicine and Komodo Health collaborate on health research using AI analytics and de-identified patient data. The research will be facilitated by the Komodo Sentinel application. It focuses on the impact of the COVID-19 pandemic on health outcomes, disparities in care, and cancer survival, treatment, and outcomes.
VirtuSense x K&B Underwriters
K&B Underwriters uses VirtuSense’s AI technology to reduce fall risks among older adults in post-acute care facilities. The technology detects the risk of falls using AI, LIDAR sensors, and laser imaging and provides immediate alerts to prevent falls. The program aims to improve long-term fall risk reduction through early detection and immediate fall prevention.
Mayo Clinic x Google Vertex AI
Google’s Vertex AI is set to be integrated into Mayo Clinic’s search platforms. As a component of this partnership, Google plans to establish a new office in close proximity to Mayo Clinic’s headquarters. The objective is to collaborate with Mayo Clinic’s medical experts and researchers, aiming to leverage Google Cloud’s data analytics and AI engineering capabilities to enhance patient care significantly. It’s worth noting that Google Cloud prioritizes compliance with HIPAA regulations and refrains from accessing or utilizing customer data for training its models.