The complexity and rise of data in healthcare means that artificial intelligence (AI) will increasingly be applied within the field. Several types of AI are already being employed by payers and providers of care, and life sciences companies. The key categories of applications involve diagnosis and treatment recommendations, patient engagement and adherence, and administrative activities. Although there are many instances in which AI can perform healthcare tasks as well or better than humans, implementation factors will prevent large-scale automation of healthcare professional jobs for a considerable period.
Machine Learning and Artificial Intelligence are the future of healthcare
Somes of the examples of areas AI & ML is being applied in Healthcare include –
Natural Language Processing (NLP) for Administrative Tasks
Patient Risk Identification
Accelerating Medical Research Insight
Visual Data Processing for Tumor Detection
Using Convolutional Neural Networks (CNNs) for Skin Cancer Diagnosis
Medical Data Science – Compliance
AI and ML is growing in Healthcare. Number of companies now use AI & ML as core to their next generation of products and services.
Artificial intelligence (AI) and related technologies are increasingly prevalent in business and society, and are beginning to be applied to healthcare. These technologies have the potential to transform many aspects of patient care, as well as administrative processes within provider, payer and pharmaceutical organizations.
PATHAI – Pathology Evolved – Advanced learning toward faster, more accurate diagnosis of disease.
Decision support & prognostic tests for high-volume specimens will mean major improvements in speed and a significant reduction in errors.
KenSci uses machine learning to predict illness and treatment to help physicians and payers intervene earlier, predict population health risk by identifying patterns and surfacing high risk markers and model disease progression and more.
Tempus is using AI to sift through the world’s largest collection of clinical and molecular data in order to personalize healthcare treatments. The company is developing AI tools that collect and analyze data in everything from genetic sequencing to image recognition, that can give physicians better insights into treatments and cures.
Allscripts Population Health Analytics™ gives providers real-time actionable insights into the health of their populations, to monitor, manage and measure.
Proscia is a digital pathology platform that uses AI to detect patterns in cancer cells. The company’s software helps pathology labs eliminate bottlenecks in data management and uses AI-powered image analysis to connect data points that support cancer discovery and treatment.
H2O.ai’s AI analyzes data throughout a healthcare system to mine, automate and predict processes. It has been used to predict ICU transfers, improve clinical workflows and even pinpoint a patient’s risk of hospital-acquired infections.
Using the company’s artificial intelligence to mine health data, hospitals can predict and detect sepsis, which ultimately reduces death rates.
ICarbonX is using AI and big data to look more closely at human life characteristics. It’s technology is focused to data to better classify symptoms, develop treatment options and get people healthier.
Vicarious Surgical combines virtual reality with AI-enabled robots so surgeons can perform minimally invasive operations. Using the company’s technology, surgeons can virtually shrink and explore the inside of a patient’s body in much more detail.