Results 51 to 60 of about 7,806,329 (300)

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

open access: yesMolecular 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   +19 more
wiley   +1 more source

Structured Prediction - Beyond Support Vector Machine and Cross Entropy

open access: yes, 2021
Presented online via Bluejeans Events on September 29, 2021 at 12:15 p.m.Francis Bach is a researcher at INRIA in the Computer Science department of Ecole Normale Supérieure, in Paris, France.
Bach, Francis
core   +1 more source

MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning

open access: yesEntropy, 2019
Efficient approximation lies at the heart of large-scale machine learning problems. In this paper, we propose a novel, robust maximum entropy algorithm, which is capable of dealing with hundreds of moments and allows for computationally efficient ...
Diego Granziol   +5 more
doaj   +1 more source

Directed evolution of enzymes at the crossroads of tradition and innovation

open access: yesFEBS 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   +2 more
wiley   +1 more source

Video-Language Critic : Transferable Reward Functions for Language-Conditioned Robotics [PDF]

open access: yes
Publisher Copyright: © 2025, Transactions on Machine Learning Research.Natural language is often the easiest and most convenient modality for humans to specify tasks for robots.
Woungang, Isaac   +6 more
core   +1 more source

A Machine Learning-Oriented Survey on Tiny Machine Learning

open access: yesIEEE Access
The emergence of Tiny Machine Learning (TinyML) has positively revolutionized the field of Artificial Intelligence by promoting the joint design of resource-constrained IoT hardware devices and their learning-based software architectures. TinyML carries an essential role within the fourth and fifth industrial revolutions in helping societies, economies,
Capogrosso, Luigi   +4 more
openaire   +5 more sources

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

open access: yesFEBS 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

DiffScale: Continuous Downscaling and Bias Correction of Subseasonal Wind Speed Forecasts Using Diffusion Models

open access: yesJournal of Advances in Modeling Earth Systems
Renewable energy generation is highly sensitive to both local and large‐scale atmospheric dynamics. Skillful subseasonal to seasonal (S2S) forecasts—ranging from 2 weeks to two months—can provide substantial socioeconomic benefits for the energy sector ...
Maximilian Springenberg   +3 more
doaj   +1 more source

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

open access: yesFEBS 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

A Multi-Objective Evaluation Framework for Analyzing Utility-Fairness Trade-Offs in Machine Learning Systems

open access: yes
The evaluation of fairness models in Machine Learning involves complex challenges, such as defining appropriate metrics, balancing trade-offs between utility and fairness, and there are still gaps in this stage. This work presents a novel multi-objective
Özbulak, Gökhan   +4 more
core   +1 more source

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