The AI healthcare industry is on the brink of a revolution, powered by rapid advancements in artificial intelligence and machine learning technologies.
As we move into 2025, these 20 companies are at the forefront, leveraging cutting-edge innovations to transform how healthcare is delivered, managed, and experienced.
From predictive analytics to personalized medicine and robotic-assisted surgeries, they’re tackling critical challenges like accessibility, accuracy, and efficiency.
These trailblazers are not just enhancing patient outcomes but are also reshaping the future of global healthcare systems. Let’s delve into the companies driving this groundbreaking evolution.
Curious about the future of AI in healthcare? Explore our latest insights here.
#1 SIEMENS HEALTHCARE GMBH
Headquarters: Erlangen, Germany
Siemens Healthcare GmbH, commonly known as Siemens Healthineers, is a global leader in medical imaging, laboratory diagnostics, and healthcare IT solutions.
It is providing advanced technologies to improve patient care and operational efficiency in healthcare systems.
Key Patents in AI in Healthcare
Incorporating Clinical And Economic Objectives For Medical Ai Deployment In Clinical Decision Making (US2023094690A1)
An AI algorithm may be used in a clinical setting to perform one or more tasks to assist medical personnel.
The results produced by the AI algorithm may affect not only patient care, but also the cost of the care.
The AI algorithm may be trained on auxiliary data to incorporate the impacts on patient care and cost.
Artificial Intelligence Dispatch In Healthcare (US2020388386A1)
Selecting the optimal artificial intelligence (AI) algorithm for a specific medical imaging task based on patient data, user constraints, and AI performance.
A multi-objective optimization is used to choose the best AI from a group of available options. This avoids applying multiple AIs and saves time and costs.
The optimization considers factors like AI performance, inclusion/exclusion criteria, cost, and user constraints. The selected AI is then applied to the medical image.
Clinical Decision Support System For Estimating Drug-Related Treatment Optimization Concerning Inflammatory Diseases (US2022310261A1)
A clinical decision support system for estimating drug-related treatment optimization in inflammatory diseases like rheumatoid arthritis.
The system uses multiple prediction models trained on patient data to select the best model for a given patient based on demographics, exam findings, medications, etc.
The selected model then predicts treatment outcomes like response, flares, side effects.
The system allows personalized treatment decisions using appropriate models tailored to the patient’s characteristics.
Method For Obtaining Disease-Related Clinical Information (EP3836157A1)
Using graph neural networks to predict disease progression, survival, and therapy response in multi-focal diseases like cancer or COPD by leveraging the spatial distribution of lesions.
The method involves representing the lesions as a graph with nodes encoding local features and edges encoding global features.
A trained graph neural network processes this graph representation to output clinical information like prognosis.
The network can handle lesions spread over the body, organs, or just one area. The graph representation can also include temporal changes.
Automated Clinical Workflow (US2021065886A1)
Various examples of embodiments of the invention generally relate to automating a clinical workflow.
The clinical workflow including an analysis of one or more medical datasets and generation of a medical report based on the analysis.
For example, machine-learning algorithms may be used for the analysis. The medical report may be generated based on one or more report templates.
Universal Health Machine For The Automatic Assessment Of Patients (US2022199254A1)
Universal health machine that uses AI to automatically assess patient health and provide personalized recommendations.
The machine interacts with patients to acquire initial data, identifies risk factors, and then further queries the patient based on the risks to gather more data.
AI models process this data to determine an assessment of the patient’s health. The machine provides diagnoses, treatment recommendations, and other actions.
Predictions For Clinical Decision Support Using Patient Specific Physiological Models (EP3905259A1)
Systems and methods for determining predictions for clinical decision support using patient specific physiological models are provided.
Patient data of a patient is received and physiologically integrated data of the patient is determined using one or more patient specific physiological models.
The one or more patient specific physiological models are personalized using the patient data.
A prediction for clinical decision making for the patient is determined based on the physiologically integrated data and the patient data using a machine learning network.
Risk Prediction For Covid-19 Patient Management (EP3905257A1)
Comprehensive risk prediction for COVID-19 patient management using machine learning on medical imaging and patient data.
The method involves extracting imaging features from CT scans, normalizing them, encoding with patient data, and feeding into a risk prediction network to assess risks like disease progression, treatment response, and resource utilization.
This provides holistic risk assessment for COVID-19 patients beyond just imaging analysis. The risk prediction network adapts based on factors like geography and time in the pandemic.
Method and device for controlling a medical device (DE102020203848A1)
A method for controlling medical devices like CT scanners that uses AI to predict patient data like cardiac cycles to improve timing and accuracy of device operation.
The method involves providing measured patient data for a first time interval, applying a trained function to estimate predicted data for a second time interval, and using the estimated data to control the medical device.
The trained function is adapted based on training data influenced by events like medication or contrast injections.
This allows more accurate predictions for unpredictable events that affect patient data.
#2 KONINKLIJKE PHILIPS NV
Headquarters: Amsterdam, Netherlands
Koninklijke Philips NV is a diversified technology company specializing in healthcare technology.
Including diagnostic imaging, connected care solutions, and health informatics, with a strong emphasis on improving lives through innovation.
Key Patents in AI in Healthcare
Method And A System For Evaluating Treatment Strategies On A Virtual Model Of A Patient (US2021241909A1)
Method to assess the impact of treatment options on virtual models of patients to help clinicians make informed decisions.
The method involves predicting and evaluating the effect of a potential treatment strategy on a virtual model of a patient.
This is done by processing the treatment information and the virtual model to predict effects like altered input data, modified output, or loss of availability.
By comparing treatment strategies’ effects, clinicians can choose one that maintains the virtual model’s accuracy during treatment.
Dynamic And Locally-Faithful Explanation Of Machine Learning Models For Precision Medicine (US2023253112A1)
Generating dynamic model explanations for a patient using simpler localized models that mimic the complex model around the patient’s changing disease states.
The technique involves calculating explanations and feature importance for each disease state using locally faithful explanation models.
Then aggregating over time or projecting into the future to provide insights into how the explanations and importance evolve as the patient’s condition changes.
This allows capturing the dynamics of a patient’s disease progression through machine learning model explanations, without the need to retrain the full model at each time point.
Patient Flow (US2020258618A1)
Improved patient flow in hospitals using machine learning to monitor and predict patient physiological status.
The system involves using a trained ML model to analyze vital sign measurements and other data to determine a patient’s physiological stability.
The model provides an output indicating the patient’s expected stability over time. This allows clinicians to identify when a patient is ready for discharge or needs escalation of care.
The ML-based stability predictions help optimize patient transitions between departments and reduce unnecessary stays.
#3 GE PRECISION HEALTHCARE LLC
Headquarters: Chicago, Illinois, USA
GE Precision Healthcare LLC delivers precision health solutions, focusing on digital tools, advanced imaging, and analytics to empower healthcare providers with actionable insights and personalized patient care strategies.
Key Patents in AI in Healthcare
Image Processing And Routing Using Ai Orchestration (WO2021003046A1)
Dynamic, study-specific generation of algorithms and processing resources for medical data using AI orchestration. It analyzes medical data and metadata to select an algorithm.
It then dynamically configures and arranges processing elements to implement the algorithm for that specific study.
This allows optimized, customized processing of medical data based on the study’s characteristics, rather than using generic algorithms.
Systems And Methods For Respiratory Support Recommendations (US2021407648A1)
Using AI to provide respiratory support recommendations for patients with conditions like COVID-19.
The AI model combines imaging features from scans like X-rays and ultrasounds with non-imaging features like vital signs and lab tests to predict ventilation needs.
It learns from longitudinal data to continuously monitor and predict intubation, extubation, and oxygen support requirements.
The AI models can also provide recommended settings for respiratory support modes.
The AI outputs are displayed along with explanations of which features contributed to the recommendations.
#4 PING AN TECHNOLOGY CO LTD
Headquarters: Shenzhen, China
Ping An Technology Co Ltd, part of Ping An Group, is a leader in AI-driven healthcare technologies, developing innovative solutions such as health management platforms, AI diagnostics, and telemedicine services to revolutionize healthcare delivery.
Key Patents in AI in Healthcare
Dynamic Intervention Method And Apparatus For Treatment Strategy, Electronic Device And Storage Medium (WO2022205601A1)
Dynamic intervention method for treatment strategies of chronic diseases that adjusts treatment plans based on patient compliance.
The method involves analyzing patient adherence to doctor orders and daily routines during treatment cycles using a compliance model.
Compliance levels are determined and treatment strategies are dynamically intervened based on pre-built rules. If compliance is high, the next cycle’s strategy is skipped.
If compliance is average, intervention is manual or intelligent. If compliance is low, the strategy is adjusted.
This allows real-time adaptation of treatment plans based on patient behavior to improve compliance and outcomes.
Method And Apparatus For Building Medical Treatment Database, And Computer Device And Storage Medium (WO2020215675A1)
Constructing a medical database with improved accuracy for medication recommendations.
The method involves using a decision tree model to output recommended treatments based on symptom inputs.
If the symptom set covers necessary features, it’s directly input. If not, related feature trajectories are found and input.
Recommended treatments are tried, scored, and high-scoring cases added to the database. This improves accuracy compared to graph traversal.
#5 INTERNATIONAL BUSINESS MACHINES CORP
Headquarters: Armonk, New York, USA
IBM Corporation is at the forefront of AI in healthcare, offering solutions like IBM Watson Health, which leverages AI to provide insights for precision medicine, drug discovery, and population health management.
Key Patents in AI in Healthcare
Automated Treatment Generation With Objective Based Learning (US2020303068A1)
Automated treatment generation system using objective-based learning to predict and generate healthcare actions that achieve specific goals like mitigating a condition.
The system uses reinforcement learning with intermediate objectives to improve accuracy and efficiency.
It records past states, actions, and rewards, evaluates action values using separate value model heads for each objective, and updates parameters based on error.
This enables rewards for achieving objectives along the way instead of just the final goal.
Pattern Discovery, Prediction And Causal Effect Estimation In Treatment Discontinuation (US2022198265A1)
Automated discovery, prediction, and causal analysis of treatment discontinuation using machine learning techniques on calendar event data.
It involves finding discriminatory sequential patterns in medication use.
It differentiate between discontinuation classes, estimating causal effects of variables on discontinuation using inverse probability weighting, and providing intervention recommendations based on the patterns and effects.
#6 BIOTRONIK SE & CO KG
Headquarters: Berlin, Germany
Biotronik SE & Co KG specializes in medical technology, particularly cardiac and vascular health solutions, including implantable devices and monitoring systems that enhance patient care and clinical outcomes.
Key Patents in AI in Healthcare
Private AI Training (US2024194347A1)
Allowing AI-based patient assessment systems to train their algorithms using local patient data without transferring sensitive data across networks.
The system involves providing computer code to a local secure data system that processes the local patient data.
The code is executed in the local system to generate training results for the AI algorithms. These results are then sent back to the assessment system for use in training.
This allows leveraging local confidential data for training AI models without exposing the data.
Computer Implemented Method For Determining A Medical Intervention, Training Method And System (WO2024099646A1)
Automated remote monitoring of cardiac current curves (ECG) to detect heart failure and recommend interventions.
It uses machine learning algorithms to classify ECG deviations, trigger patient requests for supplementary data, and determine personalized medical interventions based on combined patient data.
The method involves:
(1) ECG classification using an algorithm,
(2) requesting additional data if abnormal,
(3) using another algorithm to determine interventions based on combined ECG and supplementary data, and
(4) generating patient instructions tailored to the intervention probabilities.
#7 CANON MEDICAL SYSTEMS CORP
Headquarters: Otawara, Japan
Canon Medical Systems Corporation is a leading provider of diagnostic imaging systems and healthcare IT solutions, offering advanced technologies to improve diagnostic accuracy and patient care.
Key Patents in AI in Healthcare
Diagnosis And Treatment Support System (US2022108801A1)
A diagnosis and treatment support system that enables early detection of diseases outside a specialist’s area of expertise using machine learning models trained in other departments.
The system calculates conversion functions between different examination items based on correlations between them.
When a patient’s diagnosis and treatment data doesn’t have all the required input for a specific model, it derives missing values using the conversion functions.
This allows using models trained in other departments for diagnosis and treatment support in areas where the specialist lacks expertise.
Medical Information Processing Apparatus (EP4160619A1)
According to one embodiment, a medical information processing apparatus includes processing circuitry which updates a model for calculating an effect evaluation value for a medical decision.
The processing circuitry updates a parameter of the model while retaining the structure of the model so that the structure of the model is updated less frequently than the parameter.
#8 TOYOTA JIDOSHA KABUSHIKI KAISHA
Headquarters: Toyota City, Japan
Toyota Jidosha Kabushiki Kaisha (Toyota Motor Corporation) is exploring the integration of AI and robotics into healthcare, focusing on mobility solutions and assistive technologies for enhanced patient independence and rehabilitation.
Key Patents in AI in Healthcare
Learning System, Rehabilitation Support System, Method, Program, And Trained Model (US2020410339A1)
A learning system and rehabilitation support system that predicts changes in rehab progress for personalized coaching.
The learning system trains a model to predict how an injured person’s symptoms and recovery will progress during rehab using a rehab device.
It does this by inputting rehab data from previous sessions where symptoms reached a target level. This allows the model to learn how symptoms evolve during successful rehab.
During rehab sessions, the rehab device accesses the trained model to predict symptom changes. This provides real-time feedback to the rehab staff to optimize coaching.
Learning System, Rehabilitation Support System, Method, Program, And Trained Model (US2020410341A1)
Learning system that generates a model to predict changes in settings of a rehab device that improve training outcomes.
The model is trained using rehab data from patients whose condition improves. It can then be accessed by a rehab device during sessions to suggest optimal settings based on patient progress.
This allows staff to provide better support by checking predicted changes in settings that will improve results.
#9 SANOFI
Headquarters: Paris, France
Sanofi is a global healthcare leader focused on research and development of life-saving therapies, including vaccines and biopharmaceuticals, and leveraging AI to accelerate drug discovery and development.
Key Patent in AI in Healthcare
Methods To Estimate Effectiveness Of A Medial Treatment (US2020275885A1)
Estimating treatment effect of medical treatments using deep learning to predict responder probabilities from clinical covariates.
The method involves training a neural network model on patient data with response indicators, partitioning the response range into classes, converting response indicators to one-hot encoded vectors, and comparing probabilities of treated vs untreated subsets for each class.
#10 UNIV PRINCETON
Headquarters: Princeton, New Jersey, USA
Princeton University is a leader in academic research, contributing to healthcare innovation through AI-based solutions, including data analytics and computational modeling for disease treatment and prevention.
Key Patent in AI in Healthcare
System And Method For Intelligence Crowdsourcing Reinforcement Learning For Clinical Pathway Optimization (US2020373017A1)
Intelligent crowdsourcing reinforcement learning for healthcare applications like optimizing clinical pathways, healthcare analytics, and insurance management.
The method involves leveraging AI techniques like reinforcement learning to analyze clinical and insurance data, predict outcomes, recommend decisions, optimize pathways, and allow for analytic tools.
It uses techniques like state compression, kernel-based modeling, state abstraction, and tensor decomposition to learn optimal policies from data.
#11 ALIGN TECHNOLOGY INC
Headquarters: Tempe, Arizona, USA
Align Technology Inc specializes in innovative medical devices and digital orthodontics, including its leading Invisalign clear aligner system, powered by AI and 3D imaging technologies.
Key Patent in AI in Healthcare
Automatic Application Of Doctor’S Preferences Workflow Using Statistical Preference Analysis (WO2020191323A1)
Methods and apparatuses for automatic treatment planning, including recommendation systems, quality assurance, error prevention, text mining, text matching, and treatment planning optimization.
#12 OPTUM INC
Headquarters: Eden Prairie, Minnesota, USA
Optum Inc, a part of UnitedHealth Group, focuses on delivering integrated healthcare services, using advanced AI solutions to enhance patient care, streamline operations, and optimize health outcomes.
Key Patent in AI in Healthcare
Reinforcement Learning Machine Learning Models For Intervention Recommendation (US2023252338A1)
Efficiently performing exploration-exploitation traversal of an input space using linear computational complexity operations in reinforcement learning models.
The technique involves a novel intervention recommendation method for reinforcement learning models that selects optimal intervention routines from candidate routines by maximizing reward and minimizing loss.
Each candidate assigns a unique subset of event categories to timesteps. This enforces exploration across timesteps to traverse the input space efficiently.
#13 THE BOARD OF TRUSTEES OF THE LELAND STANFORD JUNIOR UNIVERSITY
Headquarters: Stanford, California, USA
Stanford University is a global leader in medical research and healthcare innovation, leveraging AI and machine learning to develop transformative solutions in precision medicine and diagnostics.
Key Patent in AI in Healthcare
Evaluation Of Clinical Outcome Based On Updated Probability And Related Treatments (WO2021003485A1)
Provided are methods of treatment based on prognosis as determined using a Bayesian structure. Clinical data is used in a Bayesian framework to obtain a prognosis of a medical disorder.
A prognosis can be updated using a Bayesian structure when subsequent clinical data is acquired, such as clinical data acquired during treatment or clinical monitoring.
#14 PLANNED SYSTEMS INTERNATIONAL INC
Headquarters: Columbia, Maryland, USA
Planned Systems International Inc provides advanced IT and AI-driven healthcare solutions for government and commercial clients, specializing in health informatics, data analytics, and system integration.
Key Patent in AI in Healthcare
Providing Healthcare Via Autonomous, Self-Learning, And Self-Evolutionary Processes (US2023402178A1)
Using autonomous robots to improve healthcare by enabling intelligent and adaptive decision making for patient diagnosis and treatment.
The system involves a central management system that coordinates autonomous robots to diagnose, triage, and treat patients.
The management system acquires sensor data from robots about patient conditions, uses learning models to determine diagnosis and treatment algorithms, and evolves the models based on feedback.
The robots then execute the selected algorithms. The adaptive learning improves treatment accuracy and outcomes over time.
#15 MCKESSON CORP
Headquarters: Irving, Texas, USA
McKesson Corporation is a leader in healthcare supply chain management and pharmacy services, utilizing AI and data analytics to optimize operations and improve patient care delivery.
Key Patent in AI in Healthcare
Methods, Systems, And Apparatuses For Predicting The Risk Of Hospitalization (US2021035693A1)
Methods, systems, and apparatuses for improved predictive analytics, such as patient scoring and hospitalization prediction, as described herein.
An ensemble classifier may be implemented to predict a hospitalization event for a patient based on healthcare records and demographic information associated with the patient.
The ensemble classifier may represent a plurality of machine learning models/classifiers.
The prediction generated by the ensemble classifier may be indicative or a range or likelihood that the patient will, or will not, experience a hospitalization event.
#16 RESMED SENSOR TECHNOLOGIES LTD
Headquarters: Dublin, Ireland
ResMed Sensor Technologies Ltd specializes in advanced sensor solutions and AI-powered healthcare devices, improving patient outcomes in sleep apnea and chronic respiratory conditions.
Key Patent in AI in Healthcare
Systems And Methods For Predicting The Adoption Of Therapy (WO2021064551A1)
Predicting an individual’s likelihood to adopt a prescribed medical treatment plan and generating a personalized adoption plan based on that prediction.
The prediction is made using a machine learning algorithm trained on historical data about treatment adoption.
The algorithm processes current data about the individual to determine their likelihood to follow the prescribed plan.
If high, the plan is unmodified. If low, the personalized plan may involve modifications to improve compliance.
#17 ATAI LIFE SCIENCES AG
Headquarters: Berlin, Germany
ATAI Life Sciences AG is a biopharmaceutical company pioneering mental health solutions, utilizing AI and computational biology to accelerate drug discovery and treatment development.
Key Patent in AI in Healthcare
Systems, Devices, And Methods For Event-Based Knowledge Reasoning Systems Using Active And Passive Sensors For Patient Monitoring And Feedback (WO2022236167A1)
Using machine learning models to improve treatment of disorders like mood disorders and substance use disorders.
The models analyze patient data like vital signs, responses to digital content, and surveys to monitor brain plasticity and motivation.
If levels indicate a suitable mindset, it recommends drug therapy. If adverse events are predicted, it alerts therapists and suggests content changes.
The models are trained on historical patient data to generate scores for measuring brain plasticity and motivation.
#18 CARESTREAM HEALTH INC
Headquarters: Rochester, New York, USA
Carestream Health Inc is a global provider of diagnostic imaging and healthcare IT solutions, leveraging AI to enhance imaging accuracy and streamline radiology workflows.
Key Patent in AI in Healthcare
Method Amd System To Predict Prognosis For Critically Ill Patients (WO2021141681A1)
A method for evaluating one or more diagnostic linages of a patient obtained in different examination sessions and evaluating the diagnostic images.
Using trained machine learning logic to generate prognosis and treatment information related to a medical condition of the patient detected during the evaluation.
The prognosis -related information is recorded and displayed.
#19 HOFFMANN-LA ROCHE INC
Headquarters: Basel, Switzerland
Hoffmann-La Roche Inc is a leading biopharmaceutical company, employing AI to advance drug discovery, diagnostics, and personalized healthcare solutions.
Key Patent in AI in Healthcare
Methods And Systems For Therapeutic Response Prediction (US2022122733A1)
Predicting a subject’s response to a therapeutic using recurrent neural networks trained on time-series image features and corresponding responses from previous subjects.
The method involves obtaining image data from specific timepoints after administering the therapeutic to a test subject.
A recurrent neural network trained on time-series images and responses from other subjects predicts the test subject’s response over time.
This allows predicting how the therapeutic will affect the subject without needing longitudinal data from the test subject themselves.
#20 THE GENERAL HOSPITAL CORP
Headquarters: Boston, Massachusetts, USA
The General Hospital Corporation, operating as Massachusetts General Hospital, is a leading academic medical center renowned for its comprehensive healthcare services and pioneering research in various medical fields, including the application of AI in diagnostics and treatment.
Key Patent in AI in Healthcare
Intraoperative Clinical Decision Support System (WO2020198552A1)
Real-time intraoperative clinical decision support system to enhance patient care and avoid errors in the fast-paced operating room environment.
The system provides real-time alerts and recommendations to anesthesiologists during surgery based on patient data, medication information, and vital signs.
It uses machine learning models that incorporate real-time patient data from monitors and anesthesia machines to determine if alerts should be provided.
The system also retrains the models based on user feedback and outcomes data. This allows the alerts to be tailored to patient physiology and medication context.
What’s Next for AI in Healthcare?
The future of healthcare is being transformed by AI at an unprecedented pace.
From established tech giants to agile startups, innovators are racing to revolutionize the way we diagnose, treat, and manage health conditions.
Breakthroughs in predictive analytics, precision medicine, and AI-powered diagnostics are setting the stage for a healthcare revolution that will redefine patient care.
The seamless integration of AI into healthcare systems will tackle challenges like accessibility, scalability, and efficiency, promising better outcomes for patients and providers alike.
But with so many players leading cutting-edge advancements, it’s hard to keep track of who’s driving the most change.
What if there was a way to spotlight the companies shaping the future of AI-powered healthcare?
Global Patent Search: Shaping the Future of AI in Healthcare
We are spotlighting companies leveraging AI to transform healthcare, and our Global Patent Search platform is your gateway to discovering the innovations driving this change.
With advanced search tools and analytics, you can uncover groundbreaking patents, track emerging healthcare trends, and gain a competitive edge in the industry.
From AI-powered imaging solutions to advancements in personalized medicine, our platform helps identify the technologies shaping the future of healthcare.
Stay ahead by exploring the insights and innovations revealed through Global Patent Search today.
