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A self-administered, artificial intelligence (AI) platform for cognitive assessment in multiple sclerosis (MS).
In BMC neurology
Khaligh-Razavi Seyed-Mahdi, Sadeghi Maryam, Khanbagi Mahdiyeh, Kalafatis Chris, Nabavi Seyed Massood
Artificial intelligence (AI), BICAMS, Digital biomarkers, Integrated cognitive assessment (ICA), Language-independent, Multiple sclerosis
In Telemedicine journal and e-health : the official journal of the American Telemedicine Association
Kannampallil Thomas, Ma Jun
artificial intelligence, electronic health records, m-health, pandemic, telemedicine
In Reproductive toxicology (Elmsford, N.Y.)
Challa Anup P, Beam Andrew L, Shen Min, Peryea Tyler, Lavieri Robert R, Lippmann Ethan S, Aronoff David M
chemical structure, drug development, drug exposure, high-throughput screening, informatics, machine learning, teratogenicity, translational medicine
In Journal of the American Academy of Dermatology ; h5-index 79.0
Puri Pranav, Comfere Nneka, Drage Lisa A, Shamim Huma, Bezalel Spencer A, Pittelkow Mark R, Davis Mark D P, Wang Michael, Mangold Aaron R, Tollefson Megha M, Lehman Julia S, Meves Alexander, Yiannias James A, Otley Clark C, Carter Rickey E, Sokumbi Olayemi, Hall Matthew R, Bridges Alina G, Murphree Dennis H
artificial intelligence, deep learning, dermatology, machine learning
In Journal of biomedical informatics ; h5-index 55.0
Feder Amir, Vainstein Danny, Rosenfeld Roni, Hartman Tzvika, Hassidim Avinatan, Matias Yossi
Active Machine Learning, Data Anonymization, Deep Learning, Natural Language Processing, Personally Identifiable Information
Motion artifacts reduction in brain MRI by means of a deep residual network with densely connected multi-resolution blocks (DRN-DCMB).
In Magnetic resonance imaging
Liu Junchi, Kocak Mehmet, Supanich Mark, Deng Jie
Deep leaning, Dense connection, MRI, Motion artifact, Multi-resolution block, Residual learning