Reviewing the genetics of heterogeneity in depression: operationalizations, manifestations and etiologies
With progress in genome-wide association studies of depression, from identifying zero hits
in~ 16 000 individuals in 2013 to 223 hits in more than a million individuals in 2020 …
in~ 16 000 individuals in 2013 to 223 hits in more than a million individuals in 2020 …
Dissecting diagnostic heterogeneity in depression by integrating neuroimaging and genetics
AM Buch, C Liston - Neuropsychopharmacology, 2021 - nature.com
Depression is a heterogeneous and etiologically complex psychiatric syndrome, not a
unitary disease entity, encompassing a broad spectrum of psychopathology arising from …
unitary disease entity, encompassing a broad spectrum of psychopathology arising from …
The promise of machine learning in predicting treatment outcomes in psychiatry
For many years, psychiatrists have tried to understand factors involved in response to
medications or psychotherapies, in order to personalize their treatment choices. There is …
medications or psychotherapies, in order to personalize their treatment choices. There is …
Measuring, predicting, and tracking change in psychotherapy
This chapter addresses fundamental issues of change in psychotherapy: how to measure,
monitor, predict change, and provide feedback on treatment outcome. The chapter starts …
monitor, predict change, and provide feedback on treatment outcome. The chapter starts …
Adoption of machine learning in pharmacometrics: An overview of recent implementations and their considerations
A Janssen, FC Bennis, RAA Mathôt - Pharmaceutics, 2022 - mdpi.com
Pharmacometrics is a multidisciplinary field utilizing mathematical models of physiology,
pharmacology, and disease to describe and quantify the interactions between medication …
pharmacology, and disease to describe and quantify the interactions between medication …
[HTML][HTML] Early warning signals and critical transitions in psychopathology: Challenges and recommendations
Empirical evidence is mounting that monitoring momentary experiences for the presence of
early warning signals (EWS) may allow for personalized predictions of meaningful symptom …
early warning signals (EWS) may allow for personalized predictions of meaningful symptom …
[HTML][HTML] Predicting treatment outcome in depression: an introduction into current concepts and challenges
Improving response and remission rates in major depressive disorder (MDD) remains an
important challenge. Matching patients to the treatment they will most likely respond to …
important challenge. Matching patients to the treatment they will most likely respond to …
[HTML][HTML] Systematic review of functional MRI applications for psychiatric disease subtyping
L Miranda, R Paul, B Puetz, N Koutsouleris… - Frontiers in …, 2021 - frontiersin.org
Background: Psychiatric disorders have been historically classified using symptom
information alone. Recently, there has been a dramatic increase in research interest not only …
information alone. Recently, there has been a dramatic increase in research interest not only …
[HTML][HTML] Criterion and construct validity of the Beck Depression Inventory (BDI-II) to measure depression in patients with cancer: The contribution of somatic items
S Almeida, M Camacho, JB Barahona-Corrêa… - International Journal of …, 2023 - Elsevier
Abstract Background/Objective Screening for depression in patients with cancer can be
difficult due to overlap between symptoms of depression and cancer. We assessed validity …
difficult due to overlap between symptoms of depression and cancer. We assessed validity …
[HTML][HTML] Creating sparser prediction models of treatment outcome in depression: a proof-of-concept study using simultaneous feature selection and hyperparameter …
N Rost, TM Brückl… - BMC medical …, 2022 - bmcmedinformdecismak …
Predicting treatment outcome in major depressive disorder (MDD) remains an essential
challenge for precision psychiatry. Clinical prediction models (CPMs) based on supervised …
challenge for precision psychiatry. Clinical prediction models (CPMs) based on supervised …