Results 71 to 80 of about 4,042,759 (279)

Basroparib inhibits YAP‐driven cancers by stabilizing angiomotin

Molecular Oncology, EarlyView.
Basroparib, a selective tankyrase inhibitor, suppresses Wnt signaling and attenuates YAP‐driven oncogenic programs by stabilizing angiomotin. It promotes AMOT–YAP complex formation, enforces cytoplasmic YAP sequestration, inhibits YAP/TEAD transcription, and sensitizes YAP‐active cancers, including KRAS‐mutant colorectal cancer, to MEK inhibition.
Young‐Ju Kwon, Dong Young Kim, Yuna Kim, Uk‐Il Kim, Jae‐Sung Kim   +4 more
wiley   +1 more source

Unlocking AI’s Potential

Weizenbaum Journal of the Digital Society
Rapid advances in artificial intelligence (AI) have fueled high expectations for the technology’s potential to fundamentally transform our economy and society through automation.
Peter Buxmann, Sara Ellenrieder
doaj   +1 more source

Evolutionary dynamics of the chloroplast genome in Daphne (Thymelaeaceae): comparative analysis with related genera and insights into phylogenetics

FEBS Open Bio, EarlyView.
Comparative analysis of chloroplast genomes from 14 genera of Thymelaeaceae revealed variation in gene content, ranging from 128 to 142 genes, primarily influenced by IR expansion/contraction events and pseudogenization of ndhF, ndhI, and ndhG. Two large inversions were detected within the large single‐copy region, including a synapomorphic inversion ...
Abdullah, Hui Li, Rushan Yan, Chengyu Chen, Madiha Islam, Abdul Majid, Ibrar Ahmed, Parviz Heidari, Xiaoxuan Tian   +8 more
wiley   +1 more source

State-of-the-Art in Responsible, Explainable, and Fair AI for Medical Image Analysis

IEEE Access
Integrating responsible, explainable, and fair artificial intelligence (REF-AI) into medical image analysis has gained significant attention in recent years.
Soheyla Amirian, Fengyi Gao, Nickolas Littlefield, Jonathan H. Hill, Adolph J. Yates, Johannes F. Plate, Liron Pantanowitz, Hooman H. Rashidi, Ahmad P. Tafti   +8 more
doaj   +1 more source

Blockchain and explainable AI for enhanced decision making in cyber threat detection

Software, Practice & Experience
Artificial Intelligence (AI) based cyber threat detection tools are widely used to process and analyze a large amount of data for improved intrusion detection performance.
Prabhat Kumar, Danish Javeed, Randhir Kumar, A. N. Islam   +3 more
semanticscholar   +1 more source

Navigating new norms: a systematic review of factors for the development of effective digital tools in higher education

FEBS Open Bio, EarlyView.
What factors make for an effective digital learning tool in Higher Education? This systematic review identifies elements of a digital tool that published examples reveal to be features of an engaging and impactful digital tool. A systematic literature search yielded 25 research papers for analysis.
Akmal Arzeman, Jessica Haines, Connie Pritchard, Stephen Rutherford, Nigel Francis   +4 more
wiley   +1 more source

Unexplainable Explainable AI

Synthesis philosophica, 2023
Ovaj rad kritički istražuje projekt objašnjive umjetne inteligencije (XAI). Analiziram riječ »objasniti« u XAI-ju i teoriji objašnjenja i identificiram neslaganje između značenja za »objašnjenje« za koje se tvrdi da je potrebno i onoga što je stvarno predočeno.
openaire   +1 more source

Cultural Bias in Explainable AI Research: A Systematic Analysis [PDF]

Journal of Artificial Intelligence Research
For synergistic interactions between humans and artificial intelligence (AI) systems, AI outputs often need to be explainable to people. Explainable AI (XAI) systems are commonly tested in human user studies.
Uwe Peters, Mary Carman
semanticscholar   +1 more source

TMC4 localizes to multiple taste cell types in the mouse taste papillae

FEBS Open Bio, EarlyView.
Transmembrane channel‐like 4 (TMC4), a voltage‐dependent chloride channel, plays a critical role in amiloride‐insensitive salty taste transduction. TMC4 is broadly expressed in all mature taste cell types, suggesting a possible involvement of multiple cell types in this pathway.
Momo Murata, Yoshikazu Saito, Yoichi Kasahara, Wataru Fujii, Takumi Misaka, Tomiko Asakura, Masataka Narukawa   +6 more
wiley   +1 more source

Optimized Ensemble Learning Approach with Explainable AI for Improved Heart Disease Prediction

Inf.
Recent advances in machine learning (ML) have shown great promise in detecting heart disease. However, to ensure the clinical adoption of ML models, they must not only be generalizable and robust but also transparent and explainable.
Ibomoiye Domor Mienye, N. Jere
semanticscholar   +1 more source