Results 41 to 50 of about 5,977,377 (233)

Enhancing User Trust and Interpretability in AI-Driven Feature Request Detection for Mobile App Reviews: An Explainable Approach

IEEE Access
Mobile app developers struggle to prioritize updates by identifying feature requests within user reviews. While machine learning models can assist, their complexity often hinders transparency and trust.
Ishaya Gambo, Rhodes Massenon, Chia-Chen Lin, Roseline Oluwaseun Ogundokun, Saurabh Agarwal, Wooguil Pak   +5 more
doaj   +1 more source

Conserved binding mode but diverse interfaces of MreC‐PBP2 interactions

FEBS Letters, EarlyView.
The crystal structure of abMreC reveals a conserved two β‐barrel architecture and provides structural insights into its role within the bacterial elongasome. The abMreC–abPBP2 complex model identifies the molecular basis of MreC‐mediated PBP2 recognition, contributing to the regulation of peptidoglycan synthesis.
Hyunseok Jang, Hyo Been Jin, Chang Min Kim, So Yeon Lee, Hyun Ho Park   +4 more
wiley   +1 more source

Feature Engineering in Unsupervised DNS Botnet Detectors Based on eXplainable AI

IEEE Access
Botnet communications often rely on Domain Generation Algorithms (DGAs) to establish channels among attack orchestrators and compromised hosts (bots).
Eleftheria Arkadopoulou, Nikos Kostopoulos, Maria Grammatikou, Vasilis Maglaris   +3 more
doaj   +1 more source

An epithelial GPR35 isoform supports tumor‐associated transcriptional and metabolic phenotypes

FEBS Letters, EarlyView.
GPR35 generates two functionally distinct isoforms with previously unresolved roles. GPR35‐short mediates immune‐cell chemotaxis, while GPR35‐long is enriched in colorectal cancer epithelium, where it supports increased metabolism, proliferation, and tumor‐associated transcriptional programs.
Jørgen D. Rønneberg, Martine Hjeltnes, Josephine Krieger, Joshua E. Elias, Maria Stensland, Kristian Holm, Xiaojun Jiang, Chuki Khangsar, Tuula A. Nyman, Arthur Kaser, Johannes R. Hov, Tom H. Karlsen, Nicole C. Kaneider, Frode L. Jahnsen, Georg Schneditz   +14 more
wiley   +1 more source

An interpretable and balanced machine learning framework for Parkinson's disease prediction using feature engineering and explainable AI.

PLoS ONE
Parkinson's disease (PD) is a progressive neurological disorder that affects millions globally, posing significant challenges in early and accurate diagnosis.
Nasim Mahmud Nayan, Al Mamun Rana, Md Monirul Islam, Jia Uddin, Tahmina Yasmin, Jasim Uddin   +5 more
doaj   +1 more source

Structure‐forward targeting of claudins with synthetic binders

FEBS Letters, EarlyView.
Claudins form the paracellular barriers between epithelial and endothelial tissues at tight junctions and are targets for molecular binders with the goal of modulating barrier permeability. Claudin‐binding molecules are relevant in drug delivery or in altering claudin interactions with disease‐causing proteins.
Alex J. Vecchio
wiley   +1 more source

An explainable and efficient deep learning framework for EEG-based diagnosis of Alzheimer's disease and frontotemporal dementia

Frontiers in Medicine
The early and accurate diagnosis of Alzheimer's Disease and Frontotemporal Dementia remains a critical challenge, particularly with traditional machine learning models which often fail to provide transparency in their predictions, reducing user ...
Waqar Khan, Muhammad Shahbaz Khan, Sultan Noman Qasem, Sultan Noman Qasem, Wad Ghaban, Faisal Saeed, Muhammad Hanif, Jawad Ahmad   +7 more
doaj   +1 more source

Nutrient/TOR signaling controls adipose mitochondrial transcription factor A (TFAM) to regulate organismal growth in Drosophila

FEBS Letters, EarlyView.
Animals must match their growth rate to available nutrients. We show that in Drosophila larvae, the nutrient‐sensing TOR kinase controls growth by regulating levels of TFAM, a key regulator of mitochondrial function, in the adipose tissue. When nutrients are abundant, high TOR activity suppresses TFAM, lowering mitochondrial bioenergetic activity and ...
Shrivani Sriskanthadevan‐Pirahas, Shahoon Khan, Abhishek Sharma, Byoungchun Lee, Savraj S. Grewal   +4 more
wiley   +1 more source

TensorCSBP: A Tensor Center-Symmetric Feature Extractor for EEG Odor Detection

Diagnostics
Objective: Accurate odor classification from EEG signals requires informative and interpretable features. Although Local Binary Pattern (LBP) and variants such as the center-symmetric binary pattern are widely used, they lack sufficient explainability ...
Irem Tasci, Ilknur Sercek, Yunus Talu, Prabal Datta Barua, Mehmet Baygin, Burak Tasci, Sengul Dogan, Turker Tuncer   +7 more
doaj   +1 more source

An Explainable AI Framework for Crack Width Behavior Analysis in Prestressed Concrete Beams [PDF]

预应力技术
Accurate prediction of crack width is essential for serviceability design and durability assessments of prestressed concrete structures. This study presents an explainable machine learning framework for predicting the maximum crack width of prestressed ...
Seyyedbehrad Emadi, Amir Hossein Farmanara Bozorgzad, Pooya Lotfabadi, Haiying Ma   +3 more
doaj   +1 more source