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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Identifying psychosis spectrum disorder from experience sampling data using machine learning approaches
Daniel Stamate, Andrea Katrinecz, Daniel Ståhl, et al.
Schizophrenia Research (2019) Vol. 209, pp. 156-163
Open Access | Times Cited: 19

Showing 19 citing articles:

A metabolite‐based machine learning approach to diagnose Alzheimer‐type dementia in blood: Results from the European Medical Information Framework for Alzheimer disease biomarker discovery cohort
Daniel Stamate, Min Kim, Petroula Proitsi, et al.
Alzheimer s & Dementia Translational Research & Clinical Interventions (2019) Vol. 5, Iss. 1, pp. 933-938
Open Access | Times Cited: 99
Ethics and Law in Research on Algorithmic and Data-Driven Technology in Mental Health Care: Scoping Review
Piers Gooding, Timothy Kariotis
JMIR Mental Health (2021) Vol. 8, Iss. 6, pp. e24668-e24668
Open Access | Times Cited: 51
Estimation of Potato Chlorophyll Content from UAV Multispectral Images with Stacking Ensemble Algorithm
Huanbo Yang, Yaohua Hu, Zhouzhou Zheng, et al.
Agronomy (2022) Vol. 12, Iss. 10, pp. 2318-2318
Open Access | Times Cited: 36
Application of deep and machine learning techniques for multi-label classification performance on psychotic disorder diseases
Israel Elujide, Stephen Gbenga Fashoto, Bunmi Fashoto, et al.
Informatics in Medicine Unlocked (2021) Vol. 23, pp. 100545-100545
Open Access | Times Cited: 34
Machine Learning and Non-Affective Psychosis: Identification, Differential Diagnosis, and Treatment
Maria Ferrara, Giorgia Franchini, Melissa Funaro, et al.
Current Psychiatry Reports (2022) Vol. 24, Iss. 12, pp. 925-936
Open Access | Times Cited: 15
Precision diagnostic approach to predict 5-year risk for microvascular complications in type 1 diabetes
Naba Al‐Sari, Svetlana Kutuzova, Tommi Suvitaival, et al.
EBioMedicine (2022) Vol. 80, pp. 104032-104032
Open Access | Times Cited: 11
Ecological momentary assessment (EMA) combined with unsupervised machine learning shows sensitivity to identify individuals in potential need for psychiatric assessment
Julian Wenzel, Nils Dreschke, Esther Hanssen, et al.
European Archives of Psychiatry and Clinical Neuroscience (2023) Vol. 274, Iss. 7, pp. 1639-1649
Open Access | Times Cited: 4
Understanding current states of machine learning approaches in medical informatics: a systematic literature review
Najmul Hasan, Yukun Bao
Health and Technology (2021) Vol. 11, Iss. 3, pp. 471-482
Closed Access | Times Cited: 10
Using Explainable Boosting Machine to Compare Idiographic and Nomothetic Approaches for Ecological Momentary Assessment Data
Mandani Ntekouli, Gerasimos Spanakis, Lourens Waldorp, et al.
Lecture notes in computer science (2022), pp. 199-211
Closed Access | Times Cited: 5
Use of Machine Learning Methods in Psychiatry
İlkim Ecem Emre, Cumhur Taş, Çiğdem Erol
Psikiyatride Guncel Yaklasimlar - Current Approaches in Psychiatry (2021) Vol. 13, Iss. 2, pp. 332-353
Open Access | Times Cited: 5
Artificial Intelligence in Clinical Psychology
Cosimo Tuena, Mattia Chiappini, Claudia Repetto, et al.
Elsevier eBooks (2020), pp. 10-27
Closed Access | Times Cited: 5
Predicting risk of dementia with machine learning and survival models using routine primary care records
John Langham, Daniel Stamate, Charlotte Wu, et al.
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2021), pp. 3036-3042
Open Access | Times Cited: 5
Single-label machine learning classification revealed some hidden but inter-related causes of five psychotic disorder diseases
Hilary I. Okagbue, Ogochukwu Ann Ijezie, Paulinus O. Ugwoke, et al.
Heliyon (2023) Vol. 9, Iss. 9, pp. e19422-e19422
Open Access
A metabolite-based machine learning approach to diagnose Alzheimer’s-type dementia in blood: Results from the European Medical Information Framework for Alzheimer’s Disease biomarker discovery cohort
Daniel Stamate, Min Kim, Petroula Proitsi, et al.
medRxiv (Cold Spring Harbor Laboratory) (2019)
Open Access
Tools, Technologies, and Methodologies to Support Data Science
Ricardo A. Barrera-Cámara, Ana Canepa Sáenz, Jorge A. Ruíz-Vanoye, et al.
Advances in data mining and database management book series (2020), pp. 50-72
Closed Access
Modelo computacional para apoio à decisão clínica no diagnóstico de transtornos psicóticos
Isabelle Carvalho
(2020)
Open Access
Ethics and Law in Research on Algorithmic and Data-Driven Technology in Mental Health Care: Scoping Review (Preprint)
Piers Gooding, Timothy Kariotis
(2020)
Open Access
AI and Big Data for Therapeutic Strategies in Psychiatry
Shankru Guggari
Integrated science (2022), pp. 167-181
Closed Access
Precision Diagnostic Approach to Predict 5-Year Risk for Microvascular Complications in Type 1 Diabetes
Naba Al‐Sari, Svetlana Kutuzova, Tommi Suvitaival, et al.
medRxiv (Cold Spring Harbor Laboratory) (2021)
Open Access
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