Combinatorial chemistry & high throughput screening
Jan 1, 2021
BACKGROUND: As artificial intelligence and big data analysis develop rapidly, data privacy, especially patient medical data privacy, is getting more and more attention.
Diagnostic processes typically rely on traditional and laborious methods, that are prone to human error, resulting in frequent misdiagnosis of diseases. Computational approaches are being increasingly used for more precise diagnosis of the clinical p...
Artificial intelligence (AI) is among the fastest developing areas of advanced technology in medicine. The most important qualia of AI which makes it different from other advanced technology products is its ability to improve its original program and...
Journal of the American Medical Informatics Association : JAMIA
Aug 1, 2020
OBJECTIVE: We introduce fold-stratified cross-validation, a validation methodology that is compatible with privacy-preserving federated learning and that prevents data leakage caused by duplicates of electronic health records (EHRs).
Journal of the American Medical Informatics Association : JAMIA
Jul 1, 2020
OBJECTIVE: Recent studies on electronic health records (EHRs) started to learn deep generative models and synthesize a huge amount of realistic records, in order to address significant privacy issues surrounding the EHR. However, most of them only fo...
Journal of the American Medical Informatics Association : JAMIA
Jun 1, 2020
OBJECTIVE: In this work, we introduce a privacy technique for anonymizing clinical notes that guarantees all private health information is secured (including sensitive data, such as family history, that are not adequately covered by current technique...
Cambridge quarterly of healthcare ethics : CQ : the international journal of healthcare ethics committees
Jan 1, 2020
This article considers recent ethical topics relating to medical AI. After a general discussion of recent medical AI innovations, and a more analytic look at related ethical issues such as data privacy, physician dependency on poorly understood AI he...
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2020
Typical personal medical data contains sensitive information about individuals. Storing or sharing the personal medical data is thus often risky. For example, a short DNA sequence can provide information that can identify not only an individual, but ...
Journal of the American Medical Informatics Association : JAMIA
Dec 1, 2019
OBJECTIVE: Clinical corpora can be deidentified using a combination of machine-learned automated taggers and hiding in plain sight (HIPS) resynthesis. The latter replaces detected personally identifiable information (PII) with random surrogates, allo...