Imaging biomarkers and biotypes for depression

Diagnostic and Statistical Manual of Mental Disorders

American Psychiatric Association (2013) · doi:10.1176/appi.books.9780890425596 · Cited by 116,369 · see citing works

Machine learning: Trends, perspectives, and prospects

Jordan, M. I., & Mitchell, T. M. (2015) · Science · doi:10.1126/science.aaa8415 · Cited by 9,955 · see citing works

A New Initiative on Precision Medicine

Collins, F. S., & Varmus, H. (2015) · New England Journal of Medicine · doi:10.1056/nejmp1500523 · Cited by 5,202 · see citing works

Resting-state connectivity biomarkers define neurophysiological subtypes of depression

Drysdale, A. T., Grosenick, L., Downar, J., Dunlop, K., Mansouri, F., Meng, Y., Fetcho, R. N., Zebley, B., Oathes, D. J., Etkin, A., et al. (2017) · Nature Medicine · doi:10.1038/nm.4246 · Cited by 2,170 · see citing works

On Being Sane in Insane Places

ROSENHAN, D. L. (1973) · Science · doi:10.1126/science.179.4070.250 · Cited by 2,104 · see citing works

Machine learning classifiers and fMRI: A tutorial overview

Pereira, F., Mitchell, T., & Botvinick, M. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.11.007 · Cited by 1,624 · see citing works

An fMRI-Based Neurologic Signature of Physical Pain

Wager, T. D., Atlas, L. Y., Lindquist, M. A., Roy, M., Woo, C.-W., & Kross, E. (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1204471 · Cited by 1,597 · see citing works

DSM-5 field trials in the United States and Canada, part II: test-retest reliability of selected categorical diagnoses

Regier, D. A., Narrow, W. E., Clarke, D. E., Kraemer, H. C., Kuramoto, S. J., Kuhl, E. A., & Kupfer, D. J. (2013) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2012.12070999 · Cited by 1,163 · see citing works

Developing constructs for psychopathology research: Research domain criteria

Sanislow, C. A., Pine, D. S., Quinn, K. J., Kozak, M. J., Garvey, M. A., Heinssen, R. K., Wang, P. S.-E., & Cuthbert, B. N. (2010) · Journal of Abnormal Psychology · doi:10.1037/a0020909 · Cited by 793 · see citing works

High-performance medicine: the convergence of human and artificial intelligence

Topol, E. J. (2019) · Nature Medicine · doi:10.1038/s41591-018-0300-7 · Cited by 10,450 · see citing works

Toward a neurocircuit-based taxonomy to guide treatment of obsessive-compulsive disorder

Shephard, E., Stern, E. R., van den Heuvel, O. A., Costa, D. L. C., Batistuzzo, M. C., Godoy, P. B. G., Lopes, A. C., Brunoni, A. R., Hoexter, M. Q., Shavitt, R. G., et al. (2021) · Molecular Psychiatry · doi:10.1038/s41380-020-01007-8 · Cited by 250 · see citing works

Precision behavioral phenotyping as a strategy for uncovering the biological correlates of psychopathology

Tiego, J., Martin, E. A., DeYoung, C. G., Hagan, K. E., Cooper, S. E., Pasion, R., Satchell, L. P., Shackman, A. J., Bellgrove, M. A., Fornito, A., et al. (2023) · Nature Mental Health · doi:10.1038/s44220-023-00057-5 · Cited by 118 · see citing works

Engineering Precision Medicine

Sun, W., Lee, J., Zhang, S., Benyshek, C., Dokmeci, M. R., & Khademhosseini, A. (2018) · Advanced Science · doi:10.1002/advs.201801039 · Cited by 93 · see citing works

Toward personalized medicine in connectomic deep brain stimulation

Hollunder, B., Rajamani, N., Siddiqi, S., Finke, C., Kühn, A. A., Mayberg, H. S., Fox, M., Neudorfer, C., & Horn, A. (2021) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2021.102211 · Cited by 89 · see citing works

Artificial intelligence in food science and nutrition: A narrative review

Miyazawa, T., Hiratsuka, Y., Toda, M., Hatakeyama, N., Ozawa, H., Abe, C., Cheng, T.-Y., Matsushima, Y., Miyawaki, Y., Ashida, K., et al. (2022) · Nutrition Reviews · doi:10.1093/nutrit/nuac033 · Cited by 91 · see citing works

Functional MRI in major depressive disorder: A review of findings, limitations, and future prospects

Pilmeyer, J., Huijbers, W., Lamerichs, R. M. J. N., Jansen, J. F. A., Breeuwer, M. M., & Zinger, S. (2022) · Journal of Neuroimaging · doi:10.1111/jon.13011 · Cited by 94 · see citing works

Examination of peripheral basal and reactive cortisol levels in major depressive disorder and the burnout syndrome: A systematic review

Rothe, N., Steffen, J., Penz, M. S., Kirschbaum, C., & Walther, A. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.02.024 · Cited by 83 · see citing works

Lipidomics in Major Depressive Disorder

Walther, A., Cannistraci, C. V., Simons, K., Durán, C., Gerl, M. J., Wehrli, S., & Kirschbaum, C. (2018) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2018.00459 · Cited by 77 · see citing works

Altered Resting-State Functional Connectivity of Multiple Networks and Disrupted Correlation With Executive Function in Major Depressive Disorder

Liu, Y., Chen, Y., Liang, X., Li, D., Zheng, Y., Zhang, H., Cui, Y., Chen, J., Liu, J., & Qiu, S. (2020) · Frontiers in Neurology · doi:10.3389/fneur.2020.00272 · Cited by 58 · see citing works

Inflamed brain: Targeting immune changes and inflammation for treatment of depression

Sakamoto, S., Zhu, X., Hasegawa, Y., Karma, S., Obayashi, M., Alway, E., & Kamiya, A. (2021) · Psychiatry and Clinical Neurosciences · doi:10.1111/pcn.13286 · Cited by 51 · see citing works

White Matter Abnormalities in Major Depression Biotypes Identified by Diffusion Tensor Imaging

Liang, S., Wang, Q., Kong, X., Deng, W., Yang, X., Li, X., Zhang, Z., Zhang, J., Zhang, C., Li, X., et al. (2019) · Neuroscience Bulletin · doi:10.1007/s12264-019-00381-w · Cited by 41 · see citing works

Prospective administration of anti–nerve growth factor treatment effectively suppresses functional connectivity alterations after cancer-induced bone pain in mice

Buehlmann, D., Ielacqua, G. D., Xandry, J., & Rudin, M. (2018) · Pain · doi:10.1097/j.pain.0000000000001388 · Cited by 36 · see citing works

Biotypes of HIV-associated neurocognitive disorders based on viral and immune pathogenesis

Johnson, T. P., & Nath, A. (2022) · Current Opinion in Infectious Diseases · doi:10.1097/qco.0000000000000825 · Cited by 35 · see citing works

EAG-RS: A Novel Explainability-Guided ROI-Selection Framework for ASD Diagnosis via Inter-Regional Relation Learning

Jung, W., Jeon, E., Kang, E., & Suk, H. (2023) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2023.3337362 · Cited by 30 · see citing works

Applications of Artificial Intelligence in Psychiatry and Psychology Education: Scoping Review

Prégent, J., Chung, V.-H.-A., Adib, I. E., Désilets, M., & Hudon, A. (2025) · JMIR Medical Education · doi:10.2196/75238 · Cited by 28 · see citing works

Biotypes of Central Nervous System Complications in People With Human Immunodeficiency Virus: Virology, Immunology, and Neuropathology

Joseph, S., Gianella, S., Burdo, T. H., Cinque, P. M., Gisslén, M., Letendre, S. L., Nath, A., Morgello, S., Ndhlovu, L. C., & Spudich, S. (2023) · The Journal of Infectious Diseases · doi:10.1093/infdis/jiac370 · Cited by 27 · see citing works

A dimensional approach to determine common and specific neurofunctional markers for depression and social anxiety during emotional face processing

Luo, L., Becker, B., Zheng, X., Zhao, Z., Xu, X., Zhou, F., Wang, J., Kou, J., Dai, J., & Kendrick, K. M. (2017) · Human Brain Mapping · doi:10.1002/hbm.23880 · Cited by 24 · see citing works

Amygdala and regional volumes in treatment-resistantversusnontreatment-resistant depression patients

Sandu, A., Eric Artiges, A., Galinowski, A., Gallarda, T., Bellivier, F., Lemaître, H., Granger, B., Ringuenet, D., Tzavara, E. T., Martinot, J., et al. (2017) · Depression and Anxiety · doi:10.1002/da.22675 · Cited by 23 · see citing works

A Clinician’s Perspective on Biomarkers

Rush, A. J., & Ibrahim, H. M. (2018) · FOCUS The Journal of Lifelong Learning in Psychiatry · doi:10.1176/appi.focus.20170044 · Cited by 23 · see citing works

Longitudinal resting-state functional magnetic resonance imaging in a mouse model of metastatic bone cancer reveals distinct functional reorganizations along a developing chronic pain state

Buehlmann, D., Grandjean, J., Xandry, J., & Rudin, M. (2018) · Pain · doi:10.1097/j.pain.0000000000001148 · Cited by 22 · see citing works

Major depressive disorder associated alterations in the effective connectivity of the face processing network: a systematic review

Jamieson, A. J., Leonards, C. A., Davey, C. G., & Harrison, B. J. (2024) · Translational Psychiatry · doi:10.1038/s41398-024-02734-0 · Cited by 18 · see citing works

Identification of diagnostic markers for major depressive disorder by cross-validation of data from whole blood samples

Wang, H., Zhang, M., Xie, Q., Yu, J. M., Yan, Q., & Yue, Q. (2019) · PeerJ · doi:10.7717/peerj.7171 · Cited by 15 · see citing works

Increased Functional Connectivity Between Medulla and Inferior Parietal Cortex in Medication-Free Major Depressive Disorder

Luo, L., Wu, K., Lü, Y., Gao, S., Kong, X., Lu, F., Wu, F., Wu, H., & Wang, J. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00926 · Cited by 14 · see citing works

Challenges of Machine Learning and AI (What Is Next?), Responsible and Ethical AI

Gkontra, P., Quaglio, G., Garmendia, A. T., & Lekadir, K. (2023) · Springer eBooks · doi:10.1007/978-3-031-36678-9_17 · Cited by 17 · see citing works

Abnormal Functional Connectivity of Posterior Cingulate Cortex Correlates With Phonemic Verbal Fluency Deficits in Major Depressive Disorder

Li, D., Zhang, H., Liu, Y., Liang, X., Chen, Y., Zheng, Y., Qiu, S., & Cui, Y. (2021) · Frontiers in Neurology · doi:10.3389/fneur.2021.724874 · Cited by 10 · see citing works

Artificial Intelligence and Machine Learning in Healthcare Sector

Chavda, V. P., Patel, K., Patel, S. H., & Apostolopoulos, V. (2023) · Wiley eBooks · doi:10.1002/9781119865728.ch13 · Cited by 10 · see citing works

Individual differences of maladaptive brain changes in migraine and their relationship with differential effectiveness of treatments

von Deneen, K. M., Zhao, L., & Liu, J. (2019) · Brain Science Advances · doi:10.26599/bsa.2019.9050021 · Cited by 8 · see citing works

Transcranial direct current stimulation and emotion processing deficits in psychosis and depression

Gupta, T., & Mittal, V. (2020) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/s00406-020-01146-7 · Cited by 7 · see citing works

AI (Artificial Intelligence) Transformation in Radiology: Image Diagnosis in Healthcare

Tinashe, B. P., Wu, C., & Zhou, R. (2022) · Euro-Asia Conference on Frontiers of Computer Science and Information Technology (FCSIT) · doi:10.1109/fcsit57414.2022.00042 · Cited by 5 · see citing works

Ethical issues in the application of machine learning to brain disorders

Kellmeyer, P. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-815739-8.00018-3 · Cited by 5 · see citing works

Impact of St. John’s wort extract Ze 117 on stress induced changes in the lipidome of PBMC

Bussmann, H., Bremer, S., Häberlein, H., Boonen, G., Drewe, J., Butterweck, V., & Franken, S. (2023) · Molecular Medicine · doi:10.1186/s10020-023-00644-3 · Cited by 4 · see citing works

Pharmaceutical Studies on Piperazine-based Compounds Targeting Serotonin Receptors and Serotonin Reuptake Transporters

Yamalı, C., Nenni, M., Sakarya, M. T., & Kaplan, H. A. (2024) · Mini-Reviews in Medicinal Chemistry · doi:10.2174/0113895575319878240612070850 · Cited by 4 · see citing works

Applications of Artificial Intelligence Use in Therapeutic Interventions

Carneiro, L. S. R. D. S. F., & Gomes, A. F. P. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-5072-1.ch008 · Cited by 3 · see citing works

Speech-derived acoustic biomarkers for depression: Comprehensive cross-section and longitudinal analyses in different cohorts

Lin, Y., Liyanage, B. N., Xu, C., Zhu, Z., Liao, Y., Yang, J., Tao, Y., Li, Z., Shi, C., & Yue, W. (2026) · Journal of Affective Disorders · doi:10.1016/j.jad.2026.121374 · Cited by 3 · see citing works

Shape-Based Features of White Matter Fiber-Tracts Associated with Outcome in Major Depression Disorder

Cury, C., Batail, J.-M. V., & Coloigner, J. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-16431-6_16 · Cited by 3 · see citing works

Additional file 1 of Impact of St. John’s wort extract Ze 117 on stress induced changes in the lipidome of PBMC

Bussmann, H., Bremer, S., Häberlein, H., Boonen, G., Drewe, J., Butterweck, V., & Franken, S. (2024) · Figshare · doi:10.6084/m9.figshare.26581220

Additional file 2 of Impact of St. John’s wort extract Ze 117 on stress induced changes in the lipidome of PBMC

Bussmann, H., Bremer, S., Häberlein, H., Boonen, G., Drewe, J., Butterweck, V., & Franken, S. (2024) · Figshare · doi:10.6084/m9.figshare.26581223

Additional file 3 of Impact of St. John’s wort extract Ze 117 on stress induced changes in the lipidome of PBMC

Bussmann, H., Bremer, S., Häberlein, H., Boonen, G., Drewe, J., Butterweck, V., & Franken, S. (2024) · Figshare · doi:10.6084/m9.figshare.26581226

Identification and independent validation of white matter subtypes in major depressive disorder and their role in predicting treatment response

Gao, J., Zhang, L., Wang, Y., Meng, L., Chen, X., Wang, C., Fan, Q., Zhou, J., Feng, Y., Zhou, Y., et al. (2026) · Journal of Affective Disorders · doi:10.1016/j.jad.2026.121764 · Cited by 1 · see citing works

Resting-state connectivity biomarkers define neurophysiological subtypes of depression

Drysdale, A. T., Grosenick, L., Downar, J., Dunlop, K., Mansouri, F., Meng, Y., Fetcho, R. N., Zebley, B., Oathes, D. J., Etkin, A., et al. (2017) · Nature Medicine · doi:10.1038/nm.4246 · Cited by 2,170 · see citing works

Biotype of depression from resting state brain functional connectivity

Okamoto, Y. (2019) · Asian College of Neuropsychopharmacology

33. Personalized Treatment Selection in Depression Using Clinically Interpretable Neuroimaging Biotypes

Ahn, J., Foland‐Ross, L. C., Zhang, X., Ellsay, A., Akiki, T. J., Rajasekharan, D., Holtzheimer, P. E., Lim, K. O., Madore, M. R., Philip, N. S., et al. (2026) · Biological Psychiatry · doi:10.1016/j.biopsych.2026.03.213

Parsing depression

Lewis, S. (2017) · Nature reviews. Neuroscience · doi:10.1038/nrn.2017.1 · Cited by 1 · see citing works

Evaluating the evidence for biotypes of depression: attempted replication of Drysdale et.al. 2017Preprint

Dinga, R., Schmaal, L., Penninx, B. W. J. H., van Tol, M., Veltman, D. J., van Velzen, L. S., van der Wee, N. J. A., & Marquand, A. F. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/416321 · Cited by 20 · see citing works