Medical Diagnostics
Artificial Intelligence (AI) has become one of the most transformative applications of computing in healthcare. AI systems can process and analyze vast amounts of medical data such as X-rays, MRI scans, and lab reports—faster and often more accurately than human doctors. Machine learning algorithms detect early signs of diseases such as cancer, diabetes, and heart conditions, helping clinicians make quicker and more reliable diagnoses.
For example, research by Al-Waeli and Abdul Hameed (2024) found that AI tools improved diagnostic precision and reduced medical errors by analyzing complex imaging data effectively (Wasit Journal for Pure Sciences). Similarly, Hirosawa and Shimizu (2025) reported that AI-powered systems improve workflow efficiency and personalize treatment recommendations by combining different patient data sources (Computers, Materials & Continua).
Telemedicine
Telemedicine uses computing and communication technologies to deliver healthcare remotely. Through video consultations, mobile apps, and digital monitoring devices, patients can connect with doctors regardless of physical distance. This has proven vital for people in rural and underserved regions, who may lack access to hospitals or specialists.
A 2024 study published in Frontiers in Healthcare Technology found that telemedicine significantly improved healthcare accessibility and reduced travel costs for rural patients (Frontiers in Healthcare Technology). Likewise, a PubMed study (2024) showed that telemedicine programs in rural China enhanced healthcare satisfaction and access, allowing doctors to monitor chronic conditions more effectively (PubMed Article). Computing makes these systems possible through reliable internet platforms, secure data storage, and real-time communication technologies.
Assistive Technologies
Computing also supports patients with disabilities and chronic illnesses through assistive technologies. Tools such as voice-controlled devices, AI-driven prosthetics, smart wheelchairs, and wearable sensors enable individuals to live more independently. These technologies are particularly important for monitoring vital signs and alerting caregivers in emergencies.
Philips (2021) discussed how healthcare digitalization, supported by computing, contributes to better patient experiences and sustainability by reducing unnecessary hospital visits and improving energy efficiency (Philips Blog). Assistive computing enhances the quality of life for patients while making healthcare more inclusive and responsive to diverse needs.