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Top 18 AI Use Cases in Healthcare Industry in 2024

Top 18 AI Use Cases in Healthcare Industry in 2024Top 18 AI Use Cases in Healthcare Industry in 2024

As the interest in AI in the healthcare industry continues to grow, there are numerous current AI applications in healthcare, and more use cases will emerge in the future.

We have identified the top 18 artificial intelligence use cases and vendors in the healthcare industry and structured them around typical processes that are used in the healthcare industry. 

The purpose of this article is to shed light on healthcare-related AI application cases. We, therefore, anticipate that professionals will stay informed of new developments and take into account current technologies/applications when making strategic decisions.

Patient Care

  • 2- Prescription auditing: AI audit systems can help minimize prescription errors.
  • 3- Pregnancy Management: Monitor mother and fetus to reduce mother’s worries and enable early diagnosis
  • 4- Real-timeprioritization and triage: Prescriptive analytics on patient data to enable accurate real-time case prioritization and triage. The following are some vendors in this field:
    • Jvion: The Cognitive Clinical Success Machine precisely and comprehensively foresees risk delivering the recommended actions that improve outcomes.
    • Wellframe: Wellframe flips the script by delivering interactive care programs directly to patients on a mobile device. Its portfolio of clinical modules, developed based on evidence-based care, enables the Care Team to provide a personalized experience for any patient.
    • Enlitic: Patient triaging solutions scan the incoming cases for multiple clinical findings, determine their priority, and route them to the most appropriate doctor in the network.
  • 5- Personalized medications and care: They help users to find the best treatment plans according to their patient data, thus reducing cost and increasing the effectiveness of care. The following are some of the vendors working in this field:
    • GNS Healthcare: The company uses machine learning to match the patients with the treatments that prove the most effective for them.
    • Oncora Medicals: The software structure analyzes and learns from the data that health systems have to enable them to provide personalized treatment.
  • 6- Patient Data Analytics: Analyze patient and/or 3rd party data to discover insights and suggest actions. AI allows institutions (hospitals, healthcare clinics, etc.) to analyze clinical data and generate deep insights into patient health. It provides an opportunity to reduce the cost of care, use resources efficiently, and manage population health easily. Some of the vendors specializing in patient data analytics include:
  • 7-Surgical robots: Robot-assisted surgeries combine AI and collaborative robots. These robots are well-suited for procedures that require the same repetitive movements as they can work without fatigue. AI can identify patterns within surgical procedures to improve best practices and to improve surgical robots’ control accuracy to sub-millimeter precision.

Medical Imaging and Diagnostic

  • 8- Early diagnosis: Analyze chronic conditions leveraging lab data and other medical data to enable early diagnosis
    • Ezra: Ezra leverages AI while analyzing full-body MRI scans to support clinicians in the early detection of cancer.
  • 9- Medical imaging insights: Advanced medical imaging to analyze and transform images and model possible situations.
    • SkinVision: SkinVision enables you to diagnose skin cancer early by taking photos of your skin with your phone and getting it to a doctor at the right time.
    • AI-powered medical imaging is also widely used in diagnosing COVID-19 cases and identifying patients who require ventilator support. For example, a Chinese company, Huiying Medical, has developed an AI-powered medical imaging solution with a 96% accuracy rate.

Research & Development

  • 10- Drug discovery: Find new drugs based on previous data and medical intelligence.
    • NuMedii: Biopharma company, NuMedii, has built the AIDD (Artificial Intelligence for Drug Discovery) technology that harnesses Big Data and AI to rapidly discover connections between drugs and diseases at a systematic level.
  • 11- Gene analysis and editing: Understand genes and their components. Predict the impact of gene edits.
  • 12- Device and drug comparative effectiveness
    • 4Quant: The company utilizes the latest Big Data and Deep Learning technology to extract meaningful, actionable information from images and videos for experiment design to help pick and choose which components make the most sense for the needs.

Healthcare Management

  • 13- Brand management and marketing: Create an optimal marketing strategy for the brand based on market perception and target segment.
    • Healint: The company’s product, Migraine Buddy, has recorded terabytes of data that helps patients, doctors and researchers better understand the real-world causes and effects of neurological disorders.
  • 14- Pricing and risk: Determine the optimal price for treatment and other services according to competition and other market conditions.
  • 15- Market research: Prepare hospital competitive intelligence.
    • MD Analytics: MD analytics is a global provider of health and pharmaceutical marketing research solutions.
  • 16- Operations: Process automation technologies such as intelligent automation and RPA help hospitals automate routine front-office and back-office operations such as reporting.
  • 17- Customer service chatbots: Customer service chatbots allow patients to ask questions regarding bill payment, appointments, or medication refills.
  • 18- Fraud detection: Patients may make false claims. Leveraging AI-powered fraud detection tools can help hospital managers identify fraudsters.

Other

There are too many possible AI use cases in healthcare to be listed here, and they can be identified by the practitioners. A machine learning-based solution can be built in areas where significant training data is available and the problem statement can be formulated clearly. In these areas, AI can benefit healthcare providers by:

  • Enabling data-driven decision making
  • Time & cost saving

We help companies identify partners for building such custom machine learning / AI solutions:

Identify partners to build custom AI solutions

Further reading

If you have any questions, feel free to contact us:

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Sources:

This article was originally written by former AIMultiple industry analyst Atakan Kantarci and reviewed by Cem Dilmegani

Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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