Machine learning-based definition of symptom clusters and selection of antidepressants for depressive syndrome

IB Kim, SC Park - Diagnostics, 2021 - mdpi.com
… , fifth edition (DSM-5) [13], a confirmed diagnosis of major depressive disorder requires both
… [52] demonstrated that a random forest model for therapeutic response accurately identified

Combining machine learning algorithms for prediction of antidepressant treatment response

A Kautzky, HJ Möller, M Dold, L Bartova… - Acta Psychiatrica …, 2021 - Wiley Online Library
… unfavorable treatment outcome in major depressive disorder … of treatment response and
resistance, even well-established … , a logistic regression prediction model based on a set of …

Classifying patients with depressive and anxiety disorders according to symptom network structures: A Gaussian graphical mixture model-based clustering

J Kashihara, Y Takebayashi, Y Kunisato, M Ito - Plos one, 2021 - journals.plos.org
… (eg, “Are you currently diagnosed as having major depressive disorder and being treated
for the problem in a medical setting?”). According to the responses to these items, a total of …

Identifying Parkinson's disease subtypes with motor and non-motor symptoms via model-based multi-partition clustering

…, D Weintraub, P Martinez-Martin, A Rizos, A Schrag… - Scientific Reports, 2021 - nature.com
… 17,18,19,20 , which extends model-based clustering 11 by … treatment doses 38,39 . Moreover,
as PD progresses, individuals lose their long-duration response to dopaminergic treatment

Response trajectories during escitalopram treatment of patients with major depressive disorder

JJ Nunez, YS Liu, B Cao, BN Frey, K Ho, R Milev… - Psychiatry …, 2023 - Elsevier
… We sought to investigate treatment response clusters and how they varied amongst the …
Treatment response classes in major depressive disorder identified by model-based clustering

Predicting treatment selections for individuals with major depressive disorder according to functional connectivity subgroups

X Wang, J Qin, R Zhu, S Zhang, S Tian, Y Sun… - Brain …, 2022 - liebertpub.com
model based on data-driven subgroups to provide treatment … we first identified MDD subgroups
by the hierarchical clusteringestablished a treatment prediction model to tailor treatment

Predicting non-response to multimodal day clinic treatment in severely impaired depressed patients: a machine learning approach

…, I Galatzer-Levy, H Boeker, A Brühl… - Scientific Reports, 2022 - nature.com
… techniques have been used to cluster patients with regard to … treatment aimed to (i) identify
latent subgroups of treatmentcourse of treatment), a “Responding from severe depression" …

Multimodal predictions of treatment outcome in major depression: A comparison of data-driven predictors with importance ratings by clinicians

N Rost, DB Dwyer, S Gaffron, S Rechberger… - … of Affective Disorders, 2023 - Elsevier
… We further included treatment response, defined as a … the test sample while the model based
on the 101 biological features … Using two clustering methods, we were able to identify three …

Identification of transdiagnostic psychiatric disorder subtypes using unsupervised learning

…, T Meller, K Brosch, NR Winter, A Krug… - …, 2021 - nature.com
… and targeted treatment. Our study aimed to identify psychiatric patient clusters that share …
We used high-dimensional data clustering on deep clinical data to identify transdiagnostic …

Computational approaches to treatment response prediction in major depression using brain activity and behavioral data: A systematic review

P Karvelis, CE Charlton, SG Allohverdi… - Network …, 2022 - direct.mit.edu
… emerging approach for treatment response prediction. Finally, we identify several other …
profiles, although ascertaining the clinical usefulness of the discovered clusters may require …