Privacy-preserving artificial intelligence in healthcare: Techniques and applications

There has been an increasing interest in translating artificial intelligence (AI) research into clinically-validated applications to improve the performance, capacity, and efficacy of healthcare services. Despite substantial research worldwide, very few AI-based applications have successfully made it to clinics. Key barriers to the widespread adoption of clinically validated AI applications include non-standardized medical records, limited availability of curated datasets, and stringent legal/ethical requirements to preserve patients' privacy. Therefore, there is a pressing need to improvise new data-sharing methods in the age of AI that preserve patient privacy while developing AI-based healthcare…

• QF
  Qatar Foundation
• FN
  Fonds National de la Recherche Luxembourg
• QN
  Qatar National Research Fund

  Award: 13S-0206-200273
• QN
  Qatar National Library