Suicide is one of the main preventable causes of death. Artificial intelligence (AI) could improve methods for assessing suicide risk. The objective of this review is to assess the potential of AI in identifying patients who are at risk of attempting suicide.

A systematic review of the literature was conducted on PubMed, EMBASE, and SCOPUS databases, using relevant keywords.

Thanks to this research, 296 studies were identified. Seventeen studies, published between 2014 and 2020 and matching inclusion criteria, were selected as relevant. Included studies aimed at predicting individual suicide risk or identifying at-risk individuals in a specific population. The AI performance was overall good, although variable across different algorithms and application settings.

AI appears to have a high potential for identifying patients at risk of suicide. The precise use of these algorithms in clinical situations, as well as the ethical issues it raises, remain to be clarified.

Since the description by Yaskin in 1931, it has been observed that pancreatic cancer and depression are two clinical entities that share a high affinity. This observation relies on the higher incidence of depressive syndromes associated with pancreatic cancer than in any other type of digestive tumor, and on the possible occurrence of depressive symptoms several months before the diagnosis of cancer. We present here a series of cases whose screening returned positive for depression-related diagnoses in the months prior to revelation of the cancer.

We employed a structured psychiatric interview based on DSM–IV criteria (SCID–I). The diagnoses considered were major depressive episode, minor depressive episode, and subsyndromal depression. All subjects were free of psychiatric history.

Some 15 patients were initially included: 10 presented compatible criteria for a past depressive episode, 2 presented a major depressive episode, 4 met the diagnosis of minor depression, and 4 evidenced subsyndromal depression over the one-year period prior to cancer diagnosis.

This series of cases is consistent with previous work on the subject that suggested an increased vulnerability to depressive events in the premorbid phase of pancreatic cancer. If the possibility of depressive syndromes constituting the early stages of neoplastic disease is a common idea, it is still impossible to determine the natural history of these two disorders and therefore their causal linkage.