Results 61 to 70 of about 1,130,914 (300)

Prediction of higher-selectivity catalysts by computer-driven workflow and machine learning

Science, 2019
Predicting catalyst selectivity Asymmetric catalysis is widely used in chemical research and manufacturing to access just one of two possible mirror-image products.
Andrew F. Zahrt, J. Henle, Brennan T. Rose, Yang Wang, William T. Darrow, S. Denmark   +5 more
semanticscholar   +1 more source

Rewriting the dendritic cell code in cancer—from subset identity to immunotherapeutic design

FEBS Letters, EarlyView.
Dendritic cells (DCs) play central roles in cancer immunity but are often subverted by the tumor microenvironment. This review explores the diversity of DC subsets, their functional plasticity, and emerging therapeutic strategies to reprogram DCs for enhanced antitumor responses, including vaccines, in vivo targeting, and DC‐based immunotherapies ...
Estevão Carlos Silva Barcelos, Doriana Ricciuti, Giada Mondanelli, Marco Gargaro   +3 more
wiley   +1 more source

Prepared to Design Future Technologies: Students Study How to Build Computer Systems to Think for Themselves [PDF]

, 2019
Have you ever wondered how your cell phone unlocks just by using your face? How is it able to detect the difference between your face and someone else’s?
Dell\u27Agnese, Courtney
core   +1 more source

From omics to AI—mapping the pathogenic pathways in type 2 diabetes

FEBS Letters, EarlyView.
Integrating multi‐omics data with AI‐based modelling (unsupervised and supervised machine learning) identify optimal patient clusters, informing AI‐driven accurate risk stratification. Digital twins simulate individual trajectories in real time, guiding precision medicine by matching patients to targeted therapies.
Siobhán O'Sullivan, Lu Qi, Pierre Zalloua   +2 more
wiley   +1 more source

An empirical analysis of machine learning frameworks for digital pathology in medical science

Journal of Physics: Conference Series, 2021
Digital pathology is a technology that allows pathological information created from a digital slide to be accessed, handled, and interpreted. Using optical pathology scanners, glass slides are collected and transformed to digitized glass slides that can ...
S.K.B. Sangeetha, R. Dhaya, Dhruv T Shah, R. Dharanidharan, K. S. S. Reddy   +4 more
semanticscholar   +1 more source

Exploration of heterogeneity and recurrence signatures in hepatocellular carcinoma

Molecular Oncology, EarlyView.
This study leveraged public datasets and integrative bioinformatic analysis to dissect malignant cell heterogeneity between relapsed and primary HCC, focusing on intercellular communication, differentiation status, metabolic activity, and transcriptomic profiles.
Wen‐Jing Wu, Jianchao Wang, Fuqing Chen, Xuefeng Wang, Bin Lan, Ruyi Fu, Hong Wen, Fangfang Chen, Wei Hong, Tian‐Yu Tang, Ying He, Gang Chen, Jianyin Zhou, Hai‐Long Piao, Di Chen, Shu‐Yong Lin   +15 more
wiley   +1 more source

MLnet report: training in Europe on machine learning [PDF]

, 1999
Machine learning techniques offer opportunities for a variety of applications and the theory of machine learning investigates problems that are of interest for other fields of computer science (e.g., complexity theory, logic programming, pattern ...
Ellebrecht, Mario, Morik, Katharina
core  

The Challenges of Machine Learning: A Critical Review

Electronics
The concept of learning has multiple interpretations, ranging from acquiring knowledge or skills to constructing meaning and social development. Machine Learning (ML) is considered a branch of Artificial Intelligence (AI) and develops algorithms that can
Enrico Barbierato, Alice Gatti
semanticscholar   +1 more source

Comparing self‐reported race and genetic ancestry for identifying potential differentially methylated sites in endometrial cancer: insights from African ancestry proportions using machine learning models

Molecular Oncology, EarlyView.
Integrating ancestry, differential methylation analysis, and machine learning, we identified robust epigenetic signature genes (ESGs) and Core‐ESGs in Black and White women with endometrial cancer. Core‐ESGs (namely APOBEC1 and PLEKHG5) methylation levels were significantly associated with survival, with tumors from high African ancestry (THA) showing ...
Huma Asif, J. Julie Kim
wiley   +1 more source

Cloud computing survey on services, enhancements and challenges in the era of machine learning and data science

International Journal of Informatics and Communication Technology (IJ-ICT), 2020
<p>Cloud computing has sweeping impact on the human productivity. Today it’s used for Computing, Storage, Predictions and Intelligent Decision Making, among others. Intelligent Decision Making using Machine Learning has pushed for the Cloud Services to be even more fast, robust and accurate. Security remains one of the major concerns which affect
Wajid Hassan, Te-Shun Chou, Omar Tamer, John Pickard, Patrick Appiah-Kubi, Leslie Pagliari   +5 more
openaire   +5 more sources