Results 51 to 60 of about 67,619 (257)

Interpretable Machine Learning

This thesis investigates interpretability of machine learning models from a holistic standpoint by combining optimization-based XAI methods with evaluation grounded in user studies. We propose optimization-based methods to generate rule sets for binary and multi-class classification as well as to generate (robust) counterfactual explanations for common
Mrs. M. VIJAYA, Dr. S. VENKATA LAKSHMI, Dr. M. SESHASHAYEE, Dr. R. UDAYA BHARATI, Dr. B. SUVARNA MUKHI, Dr. SHAMEEM FATIMA   +5 more
  +8 more sources

Developmental programmes drive cellular plasticity, disease progression and therapy resistance in lung adenocarcinoma

Molecular Oncology, EarlyView.
This study shows that lung adenocarcinomas exploit developmental branching morphogenesis to acquire a therapy resistant basal‐like tumour cell state. This process was found to be regulated by combined TP53 loss‐of‐function and type‐I interferon signalling, identifying a novel axis for biomarker and therapeutic target discovery.
Kamila J Bienkowska, Stephany Gallardo, Nur S. Zainal, Leena Arora, Matthew Ellis, Maria‐Antoinette Lopez, Judith Austine, Sai Pittla, Serena J Chee, Aiman Alzetani, Emily C Shaw, Christian H Ottensmeier, Gareth J Thomas, Christopher J Hanley   +13 more
wiley   +1 more source

Ensemble Interpretation: A Unified Method for Interpretable Machine Learning

CoRR, 2023
To address the issues of stability and fidelity in interpretable learning, a novel interpretable methodology, ensemble interpretation, is presented in this paper which integrates multi-perspective explanation of various interpretation methods. On one hand, we define a unified paradigm to describe the common mechanism of different interpretation methods,
Chao Min, Guoyong Liao, Guoquan Wen, Yingjun Li, Xing Guo   +4 more
openaire   +3 more sources

Gut microbiota alterations in patients with non‐small‐cell lung cancer undergoing chemoradiotherapy

Molecular Oncology, EarlyView.
We investigated the impact of concurrent chemoradiotherapy (CRT) on the gut microbiota in patients with locally advanced non‐small‐cell lung cancer. Overall gut microbiota composition remained largely stable throughout CRT while antibiotic exposure may influence microbial diversity.
Hanne Marte Nymoen, Zhi Zhao, Henrik Horndalsveen, Maria Moksnes Bjaanæs, Bjørn Henning Grønberg, Tarje Halvorsen, Tesfaye Madebo, Marianne Aanerud, Jussi Koivunen, Kersti Oselin, Saulius Cicenas, Nina Helbekkmo, Jarkko Ahvonen, Maria Silvoniemi, Tine Norman Alver, Tonje Dalen, Åsa Kristina Öjlert, Saima Jamil Farooqi, Åslaug Helland, Vilde Drageset Haakensen   +19 more
wiley   +1 more source

Directed evolution of enzymes at the crossroads of tradition and innovation

FEBS Open Bio, EarlyView.
An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova, Andrej Mirossay, Erik Sedlak   +2 more
wiley   +1 more source

From energy provision to protein synthesis: Tunnelling nanotubes as mediators of intercellular metabolic cooperation in cancer

FEBS Open Bio, EarlyView.
The cytoskeleton‐mediated transport of mitochondria via tunnelling nanotubes restores respiration, increases ATP production, rescues cells from apoptosis, activates the AKT/mTOR signalling pathway, promotes cell migration and invasiveness, contributes to cancer progression and treatment resistance.
Stanislava Martínková, Jan Trnka
wiley   +1 more source

Accurate and noninvasive prostate cancer detection using plasma‐derived extracellular vesicle RNA

FEBS Open Bio, EarlyView.
Plasma extracellular vesicles were captured with WGA‐conjugated magnetic beads and profiled for RNA biomarkers. A three‐RNA panel (NM_024955, NR_047469, and NR_002564) distinguished prostate cancer from healthy controls and benign prostatic hyperplasia, supporting a simple, noninvasive approach to improve prostate cancer detection.
Hanping Wei, Haoran Wu, Wei Feng
wiley   +1 more source

Interpretable Physics-Informed Machine Learning for Pyrolysis

Biomass
Accurate prediction of biomass pyrolysis products remains challenging due to the inherent complexity of thermochemical kinetics and the lack of mechanistic interpretability in modern Machine Learning (ML) models.
Diego Racero Galaraga, Andrea Cressoni De Conti   +1 more
doaj   +1 more source

Cell surface CD11c as a neutrophil aging marker molecule

FEBS Open Bio, EarlyView.
Cell surface CD11chi neutrophils were more aged and had better phagocytic function than CD11c−/lo neutrophils. Transcriptomic analysis of CD11chi neutrophils and CD11c−/lo neutrophils in pediatric population showed that the most difference was seen in infants.
Sophia Koutsogiannaki, Fahd Alhamdan, Erik Malm, Marie Bermudez, Samuel Y. Kim, Koichi Yuki   +5 more
wiley   +1 more source

Interpretable Clinical Decision-Making Application for Etiological Diagnosis of Ventricular Tachycardia Based on Machine Learning

Diagnostics
Background: Ventricular tachycardia (VT) can broadly be categorised into ischemic heart disease, non-ischemic structural heart disease, and idiopathic VT.
Min Wang, Zhao Hu, Ziyang Wang, Haoran Chen, Xiaowei Xu, Si Zheng, Yan Yao, Jiao Li   +7 more
doaj   +1 more source