A citation-based method for searching scientific literature

Yanmei Shen, Wenyu Zhang, Bella Siu Man Chan, Yaru Zhang, Fanchao Meng, Elizabeth A Kennon, Hanjing Emily Wu, Xuerong Luo, Xiangyang Zhang. J Affect Disord 2020
Times Cited: 6







List of co-cited articles
12 articles co-cited >1



Times Cited
  Times     Co-cited
Similarity




Reaching Those at Highest Risk for Suicide: Development of a Model Using Machine Learning Methods for use With Native American Communities.
Emily E Haroz, Colin G Walsh, Novalene Goklish, Mary F Cwik, Victoria O'Keefe, Allison Barlow. Suicide Life Threat Behav 2020
9
33

Predicting suicide attempts in adolescents with longitudinal clinical data and machine learning.
Colin G Walsh, Jessica D Ribeiro, Joseph C Franklin. J Child Psychol Psychiatry 2018
81
33

Machine Learning Based Suicide Ideation Prediction for Military Personnel.
Gen-Min Lin, Masanori Nagamine, Szu-Nian Yang, Yueh-Ming Tai, Chin Lin, Hiroshi Sato. IEEE J Biomed Health Inform 2020
9
33

Predictors of suicide attempt in patients with obsessive-compulsive disorder: an exploratory study with machine learning analysis.
Neusa Aita Agne, Caroline Gewehr Tisott, Pedro Ballester, Ives Cavalcante Passos, Ygor Arzeno Ferrão. Psychol Med 2022
7
33

Use of a Machine Learning Algorithm to Predict Individuals with Suicide Ideation in the General Population.
Seunghyong Ryu, Hyeongrae Lee, Dong-Kyun Lee, Kyeongwoo Park. Psychiatry Investig 2018
18
33

Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration.
Karel G M Moons, Douglas G Altman, Johannes B Reitsma, John P A Ioannidis, Petra Macaskill, Ewout W Steyerberg, Andrew J Vickers, David F Ransohoff, Gary S Collins. Ann Intern Med 2015
33

Classification of suicide attempters in schizophrenia using sociocultural and clinical features: A machine learning approach.
Nuwan C Hettige, Thai Binh Nguyen, Chen Yuan, Thanara Rajakulendran, Jermeen Baddour, Nikhil Bhagwat, Ali Bani-Fatemi, Aristotle N Voineskos, M Mallar Chakravarty, Vincenzo De Luca. Gen Hosp Psychiatry 2017
20
33

A Feasibility Study Using a Machine Learning Suicide Risk Prediction Model Based on Open-Ended Interview Language in Adolescent Therapy Sessions.
Joshua Cohen, Jennifer Wright-Berryman, Lesley Rohlfs, Donald Wright, Marci Campbell, Debbie Gingrich, Daniel Santel, John Pestian. Int J Environ Res Public Health 2020
6
33

Detection of Suicide Attempters among Suicide Ideators Using Machine Learning.
Seunghyong Ryu, Hyeongrae Lee, Dong-Kyun Lee, Sung-Wan Kim, Chul-Eung Kim. Psychiatry Investig 2019
4
50

Gender Differences in Machine Learning Models of Trauma and Suicidal Ideation in Veterans of the Iraq and Afghanistan Wars.
Jaimie L Gradus, Matthew W King, Isaac Galatzer-Levy, Amy E Street. J Trauma Stress 2017
27
33

Machine-learning-based diagnosis of schizophrenia using combined sensor-level and source-level EEG features.
Miseon Shim, Han-Jeong Hwang, Do-Won Kim, Seung-Hwan Lee, Chang-Hwan Im. Schizophr Res 2016
43
16

Suicide Risk Assessment Using Machine Learning and Social Networks: a Scoping Review.
Gema Castillo-Sánchez, Gonçalo Marques, Enrique Dorronzoro, Octavio Rivera-Romero, Manuel Franco-Martín, Isabel De la Torre-Díez. J Med Syst 2020
8
16

The influence of the rs6295 gene polymorphism on serotonin-1A receptor distribution investigated with PET in patients with major depression applying machine learning.
A Kautzky, G M James, C Philippe, P Baldinger-Melich, C Kraus, G S Kranz, T Vanicek, G Gryglewski, W Wadsak, M Mitterhauser,[...]. Transl Psychiatry 2017
14
16

STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies.
Patrick M Bossuyt, Johannes B Reitsma, David E Bruns, Constantine A Gatsonis, Paul P Glasziou, Les Irwig, Jeroen G Lijmer, David Moher, Drummond Rennie, Henrica C W de Vet,[...]. BMJ 2015
16

Serum miRNA as a possible biomarker in the diagnosis of bipolar II disorder.
Sheng-Yu Lee, Ru-Band Lu, Liang-Jen Wang, Cheng-Ho Chang, Ti Lu, Tzu-Yun Wang, Kuo-Wang Tsai. Sci Rep 2020
18
16


Assessing the Accuracy of Diagnostic Tests.
Fangyu Li, Hua He. Shanghai Arch Psychiatry 2018
37
16


Using the confidence interval confidently.
Avijit Hazra. J Thorac Dis 2017
42
16

Convolutional Neural Networks-Based MRI Image Analysis for the Alzheimer's Disease Prediction From Mild Cognitive Impairment.
Weiming Lin, Tong Tong, Qinquan Gao, Di Guo, Xiaofeng Du, Yonggui Yang, Gang Guo, Min Xiao, Min Du, Xiaobo Qu. Front Neurosci 2018
75
16

Association between psychological distress and mortality: individual participant pooled analysis of 10 prospective cohort studies.
Tom C Russ, Emmanuel Stamatakis, Mark Hamer, John M Starr, Mika Kivimäki, G David Batty. BMJ 2012
311
16

Combining EEG signal processing with supervised methods for Alzheimer's patients classification.
Giulia Fiscon, Emanuel Weitschek, Alessio Cialini, Giovanni Felici, Paola Bertolazzi, Simona De Salvo, Alessia Bramanti, Placido Bramanti, Maria Cristina De Cola. BMC Med Inform Decis Mak 2018
24
16

Phase-amplitude cross-frequency coupling in the human nucleus accumbens tracks action monitoring during cognitive control.
Stefan Dürschmid, Tino Zaehle, Klaus Kopitzki, Jürgen Voges, Friedhelm C Schmitt, Hans-Jochen Heinze, Robert T Knight, Hermann Hinrichs. Front Hum Neurosci 2013
16
16

A population-based cohort study of the effect of common mental disorders on disability pension awards.
Arnstein Mykletun, Simon Overland, Alv A Dahl, Steinar Krokstad, Ottar Bjerkeset, Nicholas Glozier, Leif E Aarø, Martin Prince. Am J Psychiatry 2006
165
16

Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement.
David Moher, Alessandro Liberati, Jennifer Tetzlaff, Douglas G Altman. PLoS Med 2009
16

Predicting Clinical Dementia Rating Using Blood RNA Levels.
Justin B Miller, John S K Kauwe. Genes (Basel) 2020
4
25

Suicide and Youth: Risk Factors.
Johan Bilsen. Front Psychiatry 2018
116
16

The size and burden of mental disorders and other disorders of the brain in Europe 2010.
H U Wittchen, F Jacobi, J Rehm, A Gustavsson, M Svensson, B Jönsson, J Olesen, C Allgulander, J Alonso, C Faravelli,[...]. Eur Neuropsychopharmacol 2011
16

Deep learning based low-cost high-accuracy diagnostic framework for dementia using comprehensive neuropsychological assessment profiles.
Hyun-Soo Choi, Jin Yeong Choe, Hanjoo Kim, Ji Won Han, Yeon Kyung Chi, Kayoung Kim, Jongwoo Hong, Taehyun Kim, Tae Hui Kim, Sungroh Yoon,[...]. BMC Geriatr 2018
7
16

Language in schizophrenia: relation with diagnosis, symptomatology and white matter tracts.
J N de Boer, M van Hoogdalem, R C W Mandl, J Brummelman, A E Voppel, M J H Begemann, E van Dellen, F N K Wijnen, I E C Sommer. NPJ Schizophr 2020
26
16

Risk assessment and receiver operating characteristic curves.
G Szmukler, B Everitt, M Leese. Psychol Med 2012
17
16

Data Mining Algorithms and Techniques in Mental Health: A Systematic Review.
Susel Góngora Alonso, Isabel de la Torre-Díez, Sofiane Hamrioui, Miguel López-Coronado, Diego Calvo Barreno, Lola Morón Nozaleda, Manuel Franco. J Med Syst 2018
22
16

Functional neuroimaging in mental disorders.
Philip K McGuire, Kazunori Matsumoto. World Psychiatry 2004
9
16

Mitochondrial DNA Copy Number Raises the Potential of Left Frontopolar Hemodynamic Response as a Diagnostic Marker for Distinguishing Bipolar Disorder From Major Depressive Disorder.
Noa Tsujii, Ikuo Otsuka, Satoshi Okazaki, Masaya Yanagi, Shusuke Numata, Naruhisa Yamaki, Yoshihiro Kawakubo, Osamu Shirakawa, Akitoyo Hishimoto. Front Psychiatry 2019
19
16

The treatment gap in mental health care.
Robert Kohn, Shekhar Saxena, Itzhak Levav, Benedetto Saraceno. Bull World Health Organ 2004
942
16

Generalizability of machine learning for classification of schizophrenia based on resting-state functional MRI data.
Xin-Lu Cai, Dong-Jie Xie, Kristoffer H Madsen, Yong-Ming Wang, Sophie Alida Bögemann, Eric F C Cheung, Arne Møller, Raymond C K Chan. Hum Brain Mapp 2020
15
16

Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI.
Ling-Li Zeng, Huaning Wang, Panpan Hu, Bo Yang, Weidan Pu, Hui Shen, Xingui Chen, Zhening Liu, Hong Yin, Qingrong Tan,[...]. EBioMedicine 2018
88
16

Trends in Alzheimer's disease and dementia in the asian-pacific region.
Neelum T Aggarwal, Manjari Tripathi, Hiroko H Dodge, Suvarna Alladi, Kaarin J Anstey. Int J Alzheimers Dis 2012
15
16

How to write a review article?
Ömer Gülpınar, Adil Güçal Güçlü. Turk J Urol 2013
10
16

A Systematic Literature Review of Technologies for Suicidal Behavior Prevention.
Manuel A Franco-Martín, Juan Luis Muñoz-Sánchez, Beatriz Sainz-de-Abajo, Gema Castillo-Sánchez, Sofiane Hamrioui, Isabel de la Torre-Díez. J Med Syst 2018
27
16


Assessing Suicide Risk and Emotional Distress in Chinese Social Media: A Text Mining and Machine Learning Study.
Qijin Cheng, Tim Mh Li, Chi-Leung Kwok, Tingshao Zhu, Paul Sf Yip. J Med Internet Res 2017
54
16

Classification of Unmedicated Bipolar Disorder Using Whole-Brain Functional Activity and Connectivity: A Radiomics Analysis.
Ying Wang, Kai Sun, Zhenyu Liu, Guanmao Chen, Yanbin Jia, Shuming Zhong, Jiyang Pan, Li Huang, Jie Tian. Cereb Cortex 2020
25
16

Reporting of artificial intelligence prediction models.
Gary S Collins, Karel G M Moons. Lancet 2019
254
16

EEG Frequency Bands in Psychiatric Disorders: A Review of Resting State Studies.
Jennifer J Newson, Tara C Thiagarajan. Front Hum Neurosci 2019
164
16


PARS risk charts: A 10-year study of risk assessment for cardiovascular diseases in Eastern Mediterranean Region.
Nizal Sarrafzadegan, Razieh Hassannejad, Hamid Reza Marateb, Mohammad Talaei, Masoumeh Sadeghi, Hamid Reza Roohafza, Farzad Masoudkabir, Shahram Oveisgharan, Marjan Mansourian, Mohammad Reza Mohebian,[...]. PLoS One 2017
13
16

Structural and functional neuroimaging studies of the suicidal brain.
S Desmyter, C van Heeringen, K Audenaert. Prog Neuropsychopharmacol Biol Psychiatry 2011
79
16


Co-cited is the co-citation frequency, indicating how many articles cite the article together with the query article. Similarity is the co-citation as percentage of the times cited of the query article or the article in the search results, whichever is the lowest. These numbers are calculated for the last 100 citations when articles are cited more than 100 times.