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Predicting neonatal respiratory distress syndrome and hypoglycaemia prior to discharge: Leveraging health administrative data and machine learning.
In Journal of biomedical informatics ; h5-index 55.0
Betts Kim S, Kisely Steve, Alati Rosa
Administrative data linkage, machine learning, neonatal outcomes, predictive models
Identification of specific neural circuit underlying the key cognitive deficit of remitted late-onset depression: A multi-modal MRI and machine learning study.
In Progress in neuro-psychopharmacology & biological psychiatry
Wang Zan, Yuan Yonggui, Jiang Ying, You Jiayong, Zhang Zhijun
Cognitive deficit, Late-onset depression, Machine learning, Magnetic resonance imaging, Relevance vector regression
In Journal of biotechnology
Ulfenborg Benjamin, Karlsson Alexander, Riveiro Maria, Andersson Christian X, Sartipy Peter, Synnergren Jane
Clustering, K-means, annotation enrichment, multiple cluster assignment, pathways, transcriptomics
Exploring dyserythropoiesis in patients with myelodysplastic syndrome by imaging flow cytometry and machine-learning assisted morphometrics.
In Cytometry. Part B, Clinical cytometry
Rosenberg Carina A, Bill Marie, Rodrigues Matthew A, Hauerslev Mathias, Kerndrup Gitte B, Hokland Peter, Ludvigsen Maja
dyserythropoiesis, high-throughput morphometric quantification, imaging flow cytometry, myelodysplastic syndrome
Deep Learning-assisted MRI Prediction of Tumor Response to Chemotherapy in Patients with Colorectal Liver Metastases.
In International journal of cancer ; h5-index 82.0
Zhu Hai-Bin, Xu Da, Ye Meng, Sun Li, Zhang Xiao-Yan, Li Xiao-Ting, Nie Pei, Xing Bao-Cai, Sun Ying-Shi
colorectal liver metastases, deep learning, magnetic resonance imaging, tumor regression grade
In Surgery ; h5-index 54.0
Rogers Michael P, DeSantis Anthony J, Janjua Haroon, Barry Tara M, Kuo Paul C