Machine learning for multi-omics data integration in cancer
Multi-omics data analysis is an important aspect of cancer molecular biology studies and
has led to ground-breaking discoveries. Many efforts have been made to develop machine …
has led to ground-breaking discoveries. Many efforts have been made to develop machine …
Machine learning‐enabled smart sensor systems
Recent advancements and major breakthroughs in machine learning (ML) technologies in
the past decade have made it possible to collect, analyze, and interpret an unprecedented …
the past decade have made it possible to collect, analyze, and interpret an unprecedented …
Deepdrid: Diabetic retinopathy—grading and image quality estimation challenge
We described a challenge named" Diabetic Retinopathy (DR)—Grading and Image Quality
Estimation Challenge" in conjunction with ISBI 2020 to hold three sub-challenges and …
Estimation Challenge" in conjunction with ISBI 2020 to hold three sub-challenges and …
MOLI: multi-omics late integration with deep neural networks for drug response prediction
Motivation Historically, gene expression has been shown to be the most informative data for
drug response prediction. Recent evidence suggests that integrating additional omics can …
drug response prediction. Recent evidence suggests that integrating additional omics can …
Momentum contrastive learning for few-shot COVID-19 diagnosis from chest CT images
The current pandemic, caused by the outbreak of a novel coronavirus (COVID-19) in
December 2019, has led to a global emergency that has significantly impacted economies …
December 2019, has led to a global emergency that has significantly impacted economies …
Strengths and weaknesses of deep learning models for face recognition against image degradations
Convolutional neural network (CNN) based approaches are the state of the art in various
computer vision tasks including face recognition. Considerable research effort is currently …
computer vision tasks including face recognition. Considerable research effort is currently …
Face recognition by humans and machines: three fundamental advances from deep learning
Deep learning models currently achieve human levels of performance on real-world face
recognition tasks. We review scientific progress in understanding human face processing …
recognition tasks. We review scientific progress in understanding human face processing …
A comprehensive analysis of deep learning based representation for face recognition
M Mehdipour Ghazi… - Proceedings of the IEEE …, 2016 - cv-foundation.org
Deep learning based approaches have been dominating the face recognition field due to
the significant performance improvement they have provided on the challenging wild …
the significant performance improvement they have provided on the challenging wild …
[HTML][HTML] Computational pathology: a survey review and the way forward
Abstract Computational Pathology (CPath) is an interdisciplinary science that augments
developments of computational approaches to analyze and model medical histopathology …
developments of computational approaches to analyze and model medical histopathology …
Data compression and inference in cosmology with self-supervised machine learning
A Akhmetzhanova, S Mishra-Sharma… - Monthly Notices of the …, 2024 - academic.oup.com
The influx of massive amounts of data from current and upcoming cosmological surveys
necessitates compression schemes that can efficiently summarize the data with minimal loss …
necessitates compression schemes that can efficiently summarize the data with minimal loss …