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Evidence record 1993 · automatically gathered

Supervised machine learning classifiers for schizophrenia and bipolar disorder using speech and language: a systematic review, meta-analysis, and novel quality assessment framework

This paper presents a systematic review and meta-analysis of 62 studies that developed speech- and language-based AI for severe mental illnesses (SMI) (i.e., characterized by substantial communication problems affecting speech production and language). We employed a random-effects meta-analysis using Restricted Maximum Likelihood (REML). We evaluated these studies using our proposed rigorous 16-item quality assessment framework, grouped into three domains: Study Design, Fairness and Explainabili

Record details

Published: 29 June 2026
Source: Artificial Intelligence Review
Category: Research
Topics: Bias & fairness · Transparency
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

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How to cite this record

ethics.ai (29 June 2026), “Supervised machine learning classifiers for schizophrenia and bipolar disorder using speech and language: a systematic review, meta-analysis, and novel quality assessment framework,” evidence record 1993, https://ethics.ai/record/1993 (originally published by Artificial Intelligence Review).

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