Artificial intelligence (AI) is transforming the way healthcare is being delivered. AI is an overarching term used to describe the use of machine-learning algorithms and software to mimic human cognition in the analysis, presentation, and comprehension of complex medical and health care data³. AI has shown promise in various areas of healthcare, such as clinical, administrative, and research applications. In this post, we will explore some of the ways AI could improve the healthcare industry and provide better outcomes for patients and providers.
Clinical applications of AI
Clinical applications of AI are those that directly affect the diagnosis, treatment, and care of patients. Some of the clinical applications of AI include:
- Predicting health trajectories of patients: AI tools can use data from health records, images, population data, claims data, and clinical trial data to analyze patterns and trends that can help predict the risk of developing certain diseases or complications, the progression of existing conditions, or the response to treatments¹. For example, IBM Watson Health has developed an AI tool that can predict the risk of heart failure for patients with diabetes¹.
- Recommending treatments: AI tools can use data from various sources to suggest the best course of action for a patient based on their medical history, symptoms, preferences, and evidence-based guidelines¹. For example, IBM Watson for Oncology can provide treatment recommendations for cancer patients based on their genomic profile and the latest medical literature¹.
- Guiding surgical care: AI tools can assist surgeons in performing complex procedures by providing real-time feedback, guidance, or automation¹. For example, Intuitive Surgical has developed a robotic surgical system that uses AI to enhance the precision and dexterity of surgeons¹.
- Monitoring patients: AI tools can monitor patients' vital signs, symptoms, behaviors, or activities using sensors, wearables, or mobile devices¹. For example, Biofourmis has developed an AI-powered platform that can remotely monitor patients with chronic conditions and alert clinicians if their condition worsens¹.
- Supporting population health management: AI tools can help healthcare organizations improve the health outcomes of a community by identifying high-risk groups, providing preventive interventions, or optimizing resource allocation¹. For example, Health Catalyst has developed an AI-driven platform that can help healthcare organizations identify gaps in care, reduce readmissions, and lower costs¹.
Administrative applications of AI
Administrative applications of AI are those that affect the efficiency and quality of healthcare operations and processes. Some of the administrative applications of AI include:
- Recording digital notes: AI tools can use natural language processing (NLP) to transcribe speech or text into structured data that can be stored in electronic health records (EHRs) or other systems¹. For example, Nuance has developed an AI-powered solution that can capture clinical documentation from voice or text input and automatically populate EHRs¹.
- Optimizing operational processes: AI tools can use data from various sources to analyze and improve the performance of healthcare workflows, such as scheduling appointments, managing inventory, or allocating staff¹. For example, LeanTaaS has developed an AI-powered platform that can optimize the utilization of operating rooms, infusion centers, or clinics¹.
- Automating laborious tasks: AI tools can use computer vision or robotics to perform tasks that are tedious or repetitive for humans, such as scanning images, sorting samples, or dispensing medications¹. For example, Zebra Medical Vision has developed an AI tool that can automatically detect abnormalities in medical images¹.
Research applications of AI
Research applications of AI are those that support the discovery and development of new knowledge or innovations in healthcare. Some of the research applications of AI include:
- Developing drugs: AI tools can use data from various sources to accelerate the drug discovery and development process by identifying potential targets, designing molecules, screening compounds, or predicting outcomes¹. For example,
BenevolentAI has developed an AI platform that can generate novel drug candidates for various diseases¹.
- Personalizing medicine: AI tools can use data from various sources to tailor treatments or interventions to individual patients based on their genetic profile, biomarkers,
or preferences¹. For example,
Tempus has developed an AI platform that can provide personalized cancer care based on genomic sequencing and clinical data¹.
- Conducting clinical trials: AI tools can use data from various sources to facilitate the design,
execution,
and analysis of clinical trials by selecting participants,
(1) Artificial intelligence in healthcare - Wikipedia. https://en.wikipedia.org/wiki/Artificial_intelligence_in_healthcare.
(2) What is artificial intelligence in healthcare? | IBM. https://www.ibm.com/topics/artificial-intelligence-healthcare.
(3) Artificial Intelligence in Health Care: Benefits and Challenges of .... https://www.gao.gov/products/gao-21-7sp.
(4) AI in Health Care: Applications, Benefits, and Examples. https://www.coursera.org/articles/ai-in-health-care.
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