Psychiatric illnesses are heterogeneous in nature. No illness manifests in the same way across individuals, and no two patients with a shared diagnosis exhibit identical symptom profiles. Over the last several decades, group-level analyses of in vivo...
BACKGROUND: Developing predictive models for precision psychiatry is challenging because of unavailability of the necessary data: extracting useful information from existing electronic health record (EHR) data is not straightforward, and available cl...
Annals of the New York Academy of Sciences
Mar 1, 2022
Disruptive innovation is a cornerstone of various disciplines, particularly in the business world, where paradigm-altering approaches are often lauded. As a construct, disruptive psychiatry can be considered to embody such an approach by the pursuit ...
Methods used in artificial intelligence (AI) overlap with methods used in computational psychiatry (CP). Hence, considerations from AI ethics are also relevant to ethical discussions of CP. Ethical issues include, among others, fairness and data owne...
Digitalization and artificial intelligence hold the prospect of new procedures for psychiatry. Machine learning techniques combined with big data should enable algorithmized diagnostics, prediction and therapy that are superior to clinical observatio...
The clinical interview is the psychiatrist's data gathering procedure. However, the clinical interview is not a defined entity in the way that 'vitals' are defined as measurements of blood pressure, heart rate, respiration rate, temperature, and oxyg...
Nederlands tijdschrift voor geneeskunde
Mar 25, 2021
The clinical application of neuroimaging for psychological complaints has so far been limited to the exclusion of somatic pathology. Radiological assessment of brain scans usually does not explain the psychological symptoms. However, that does not me...
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