Deployed Skills and Abilities: A Look at Our Capacities
The global digital healthcare market is predicted to reach $275 billion by 2028, with opportunities particularly in early diagnosis and reducing errors in medical services. Despite these advancements, the industry requires continued exploration and innovation to address existing gaps and technical challenges, such as network disruptions or software glitches.
Recent breakthroughs, such as robotic-assisted surgeries using the da Vinci Surgical System and AI-driven diagnostic tools like PathAI, indicate a future where AI seamlessly integrates into medical workflows, enhancing diagnoses, treatment plans, and patient interactions.
This report explores digital healthcare trends anticipated in 2025, focusing on driving factors, leading companies, and future outlook.
Integration of Artificial Intelligence in the Digital Healthcare Industry
AI-Based Diagnostic Assistance
With the surge in digital health data and the exponential growth in computational power, tools like PathAI are binding AI into the core of medical diagnostics. Multiple startups, universities, and industry giants like Siemens Healthcare Diagnostics, Fujifilm, and Philips have developed diagnostic support systems for disease diagnosis through image data.
Recent Developments in AI-Based Diagnostic Assistance
In 2022, researchers at Stanford Medicine, including Dr. Gary Peltz and Dr. Zhuoqing Fang, developed an AI program that accelerates the identification of disease-associated genes. This automated pipeline efficiently processes vast genomic data and scientific literature, transforming a process that typically took months into a significantly faster and more streamlined operation. Successful applications include identifying genes linked to diabetes, obesity, and cataracts in mice.
Recent Collaborations in AI-Based Diagnostic Assistance
Enhancing Radiology Operations
Enlitic, a healthcare IT company, has partnered with GE Healthcare to enhance operational efficiency for radiologists worldwide. GE will integrate Enlitic's AI-based Curie platform into its workflow, promoting data standardization and system efficiency.
The AI-powered data normalization reduces radiologists' non-diagnostic tasks, streamlining workflows for improved outcomes.
Colonoscopy Tool to Aid Physicians
NVIDIA has partnered with Medtronic, a leading healthcare technology provider, to incorporate NVIDIA's healthcare and edge AI technologies into Medtronic's GI Genius intelligent endoscopy module, developed by Cosmo Pharmaceuticals. Notably, GI Genius is the first FDA-cleared, AI-assisted colonoscopy tool designed to aid physicians in detecting polyps that may lead to colorectal cancer.
Image Analysis Workflow for Pathologists
Roche partnered with PathAI, a global AI-powered pathology technology leader, to create an embedded image analysis workflow for pathologists. This integration enables access to PathAI's image analysis algorithms within NAVIFY Digital Pathology, Roche's cloud-based uPath enterprise software.
Enhancing Cancer Diagnosis
Roche further partnered with Bristol Myers Squibb to advance two assays for clinical trials by developing and deploying innovative digital pathology algorithms. The collaboration aims to utilize data from both projects to enhance cancer diagnosis and further personalized healthcare treatment options.
Secured Integration of Administrative Tools and Clinical Insights
Microsoft and Epic, a medical software development company, collaborated to address clinician challenges, such as cumbersome documentation processes and time-consuming administrative tasks, by integrating AI technologies into the Epic electronic health record (EHR) ecosystem. The expansion aims to accelerate the development of AI-powered solutions, providing secure access to clinical insights and administrative tools within various Epic modules. The goal is to enhance patient care, improve operational efficiency, elevate healthcare experiences, and bolster the financial integrity of global health systems.
AI-Based Disease Treatment and Prediction
As predicted by the Journal of Medicine, healthcare providers face a nationwide shortage of 90,000 physicians by 2025. Simultaneously, they grapple with financial pressures to deliver quality care. AI is a valuable solution in this challenging landscape, extending its assistance beyond diagnostics and providing personalized treatment recommendations based on factors like genetics, lifestyle, and environment. A prime example is Tempus, which analyzes clinical and molecular data using AI, offering personalized care for cancer patients.
Recent Developments in AI-Based Disease Treatment and Prediction
The groundbreaking innovation by Northwestern Medicine surpassed expert pathologists in predicting disease courses, which may save breast cancer patients from unnecessary chemotherapy. Analyzing both cancerous and non-cancerous cells, this AI model showcases the significance of non-cancer components in determining patient outcomes.
Recent Collaborations in AI-Based Disease Treatment and Prediction
Risk Assessment of Neurological Diseases
Nippon Telegraph and Telephone (NTT) have recently collaborated with the National Center for Neurology and Psychiatry to develop Brain Bio-Digital Twin" technology in 2024. Over the next three years, they will focus on researching the brain and associated diseases. They plan to collaborate with pharmaceutical companies to develop effective medications and establish a system to detect and prevent mental illnesses at an early stage.
Early Detection of Cardiovascular Diseases
A biotech research firm, Tempus, and US-based healthcare provider, Geisinger, collaborated on a machine learning-based method to assess cardiology disease risk. A composite model generates individual risk scores for specific conditions by analyzing ECG trace data and clinical information. Combining these yields a composite risk score, which indicates the likelihood of developing specified cardiology diseases within a timeframe. The system factors in age, gender, vitals, lab results, and comorbidities, prompting additional tests if the risk score surpasses a threshold—improving early detection and treatment.
In the following sections, we will discuss the trends in wearable devices and regenerative medicine shaping the digital healthcare landscape.
- Researchers at Stanford Medicine have developed an AI program that accelerates the identification of disease-associated genes, streamlining a time-consuming process and successfully applying it to identify genes linked to diabetes, obesity, and cataracts in mice.
- Tempus, a company that analyzes clinical and molecular data using AI, offers personalized care for cancer patients by analyzing various factors like genetics, lifestyle, and environment to provide personalized treatment recommendations.
