IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Feb 25, 2021
In myoelectric machine learning (ML) based control, it has been demonstrated that control performance usually increases with training, but it remains largely unknown which underlying factors govern these improvements. It has been suggested that the i...
Deep learning has emerged as a revolutionary technology for protein residue-residue contact prediction since the 2012 CASP10 competition. Considerable advancements in the predictive power of the deep learning-based contact predictions have been achie...
A primary challenge in single-cell RNA sequencing (scRNA-seq) studies comes from the massive amount of data and the excess noise level. To address this challenge, we introduce an analysis framework, named single-cell Decomposition using Hierarchical ...
PURPOSE: Accurate segmentation of lung and infection in COVID-19 computed tomography (CT) scans plays an important role in the quantitative management of patients. Most of the existing studies are based on large and private annotated datasets that ar...
IEEE transactions on neural networks and learning systems
Feb 4, 2021
Multitask learning (MTL) aims at solving the related tasks simultaneously by exploiting shared knowledge to improve performance on individual tasks. Though numerous empirical results supported the notion that such shared knowledge among tasks plays a...
IEEE transactions on neural networks and learning systems
Feb 4, 2021
Brain tumor is one of the most dangerous cancers in people of all ages, and its grade recognition is a challenging problem for radiologists in health monitoring and automated diagnosis. Recently, numerous methods based on deep learning have been pres...
IEEE transactions on neural networks and learning systems
Feb 4, 2021
Person re-identification (re-ID) favors discriminative representations over unseen shots to recognize identities in disjoint camera views. Effective methods are developed via pair-wise similarity learning to detect a fixed set of region features, whi...
Protein structure prediction is a long-standing unsolved problem in molecular biology that has seen renewed interest with the recent success of deep learning with AlphaFold at CASP13. While developing and evaluating protein structure prediction metho...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 25, 2021
Recent medical prognostic models adapted from high data-resource fields like language processing have quickly grown in complexity and size. However, since medical data typically constitute low data-resource settings, performances on tasks like clinic...
Neural networks : the official journal of the International Neural Network Society
Jan 14, 2021
Feature selection is an important issue in machine learning and data mining. Most existing feature selection methods are greedy in nature thus are prone to sub-optimality. Though some global feature selection methods based on unsupervised redundancy ...