Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation

Search Page

My NCBI Filters
Results by year

Table representation of search results timeline featuring number of search results per year.

Year Number of Results
2016 2
2017 1
2018 2
2019 2
2020 1
Text availability
Article attribute
Article type
Publication date

Search Results

6 results
Results by year

Citations

1 article found by citation matching

Search results

Filters applied: . Clear all
Page 1
Prediction of Individual Response to Electroconvulsive Therapy via Machine Learning on Structural Magnetic Resonance Imaging Data.
Redlich R, Opel N, Grotegerd D, Dohm K, Zaremba D, Bürger C, Münker S, Mühlmann L, Wahl P, Heindel W, Arolt V, Alferink J, Zwanzger P, Zavorotnyy M, Kugel H, Dannlowski U. Redlich R, et al. JAMA Psychiatry. 2016 Jun 1;73(6):557-64. doi: 10.1001/jamapsychiatry.2016.0316. JAMA Psychiatry. 2016. PMID: 27145449 Clinical Trial.
IMPORTANCE: Electroconvulsive therapy (ECT) is one of the most effective treatments for severe depression. However, biomarkers that accurately predict a response to ECT remain unidentified. ...CONCLUSIONS AND RELEVANCE: A relatively small degree of structural …
IMPORTANCE: Electroconvulsive therapy (ECT) is one of the most effective treatments for severe depression. However, biomarkers …
Local functional connectivity density is closely associated with the response of electroconvulsive therapy in major depressive disorder.
Wang J, Wei Q, Yuan X, Jiang X, Xu J, Zhou X, Tian Y, Wang K. Wang J, et al. J Affect Disord. 2018 Jan 1;225:658-664. doi: 10.1016/j.jad.2017.09.001. Epub 2017 Sep 6. J Affect Disord. 2018. PMID: 28910748
BACKGROUND: Electroconvulsive therapy (ECT) has been demonstrated to be an effective treatment of major depressive disorder (MDD). ...In addition, the identified neural indices as classification characteristics were entered into multivariate pattern analysis
BACKGROUND: Electroconvulsive therapy (ECT) has been demonstrated to be an effective treatment of major depressive disorder (M …
Predicting individual responses to the electroconvulsive therapy with hippocampal subfield volumes in major depression disorder.
Cao B, Luo Q, Fu Y, Du L, Qiu T, Yang X, Chen X, Chen Q, Soares JC, Cho RY, Zhang XY, Qiu H. Cao B, et al. Sci Rep. 2018 Apr 3;8(1):5434. doi: 10.1038/s41598-018-23685-9. Sci Rep. 2018. PMID: 29615675 Free PMC article.
We applied a machine learning algorithm to the hippocampal subfield volumes at baseline and were able to predict the change in depressive symptoms (r = 0.81; within remitters, r = 0.93). Receiver operating characteristic analysis also showed robust prediction …
We applied a machine learning algorithm to the hippocampal subfield volumes at baseline and were able to predict the change in …
Prediction of individual responses to electroconvulsive therapy in patients with schizophrenia: Machine learning analysis of resting-state electroencephalography.
Min B, Kim M, Lee J, Byun JI, Chu K, Jung KY, Lee SK, Kwon JS. Min B, et al. Schizophr Res. 2020 Feb;216:147-153. doi: 10.1016/j.schres.2019.12.012. Epub 2019 Dec 26. Schizophr Res. 2020. PMID: 31883932
BACKGROUND: Electroconvulsive therapy (ECT) has strong efficacy in patients with treatment refractory schizophrenia. However, access to ECT has been limited by high costs, professional labor, treatment duration, and significant adverse effects. To provide support fo …
BACKGROUND: Electroconvulsive therapy (ECT) has strong efficacy in patients with treatment refractory schizophrenia. However, …
[Neuronal effects and biomarkers of antidepressant treatments : Current review from the perspective of neuroimaging].
Enneking V, Dzvonyar F, Dannlowski U, Redlich R. Enneking V, et al. Nervenarzt. 2019 Mar;90(3):319-329. doi: 10.1007/s00115-019-0675-9. Nervenarzt. 2019. PMID: 30729991 Review. German.
By the identification of neuroanatomical markers, baseline volumes of the ACC have also been shown to be associated with therapy response to all treatments. The identification of such neuronal biomarkers in combination with machine learning techniques …
By the identification of neuroanatomical markers, baseline volumes of the ACC have also been shown to be associated with therapy r
Feedback