Results 61 to 70 of about 4,042,759 (279)

In vitro models of cancer‐associated fibroblast heterogeneity uncover subtype‐specific effects of CRISPR perturbations

Molecular Oncology, EarlyView.
Development of therapies targeting cancer‐associated fibroblasts (CAFs) necessitates preclinical model systems that faithfully represent CAF–tumor biology. We established an in vitro coculture system of patient‐derived pancreatic CAFs and tumor cell lines and demonstrated its recapitulation of primary CAF–tumor biology with single‐cell transcriptomics ...
Elysia Saputra, Shamsudheen Karuthedath Vellarikkal, Lixia Li, Hong Sun, Khoa Nguyen, Amber Montano, Suchitra Natarajan, Federica Piccioni, Alex Michael Tamburino, Xin Yu, Aleksandra Katarzyna Olow   +10 more
wiley   +1 more source

E-XAI: Evaluating Black-Box Explainable AI Frameworks for Network Intrusion Detection

IEEE Access
The exponential growth of intrusions on networked systems inspires new research directions on developing artificial intelligence (AI) techniques for intrusion detection systems (IDS).
Osvaldo Arreche, Tanish Guntur, Jack W. Roberts, Mustafa Abdallah   +3 more
semanticscholar   +1 more source

Transcriptional network analysis of PTEN‐protein‐deficient prostate tumors reveals robust stromal reprogramming and signs of senescent paracrine communication

Molecular Oncology, EarlyView.
Combining PTEN protein assessment and transcriptomic profiling of prostate tumors, we uncovered a network enriched in senescence and extracellular matrix (ECM) programs associated with PTEN loss and conserved in a mouse model. We show that PTEN‐deficient cells trigger paracrine remodeling of the surrounding stroma and this information could help ...
Ivana Rondon‐Lorefice, Jose I. Lopez, Aitziber Ugalde‐Olano, Maite Zufiaurre, Ianire Astobiza, Natalia Martin‐Martin, Laura Bozal‐Basterra, Saioa Garcia‐Longarte, Amaia Zabala‐Letona, Sofia Rey, Aida Santos‐Martin, Miguel Unda, Ana Loizaga‐Iriarte, Mariona Graupera, Paolo Nuciforo, Arkaitz Carracedo, Isabel Mendizabal   +16 more
wiley   +1 more source

Explainable Artificial Intelligence Models for Predicting Depression Based on Polysomnographic Phenotypes

Bioengineering
Depression is a common mental health disorder and a leading contributor to mortality and morbidity. Despite several advancements, the current screening methods have limitations in enabling the robust and automated detection of depression, thereby ...
Doljinsuren Enkhbayar, Jaehoon Ko, Somin Oh, Rumana Ferdushi, Jaesoo Kim, Jaehong Key, Erdenebayar Urtnasan   +6 more
doaj   +1 more source

Explainable AI for 6G Use Cases: Technical Aspects and Research Challenges

IEEE Open Journal of the Communications Society
Around 2020, 5G began its commercialization journey, and discussions about the next-generation networks (such as 6G) emerged. Researchers predict that 6G networks will have higher bandwidth, coverage, reliability, energy efficiency, and lower latency ...
Shen Wang, Muhammad Atif Qureshi, Luis Miralles-Pechuán, Thien Huynh-The, T. Gadekallu, Madhusanka Liyanage   +5 more
semanticscholar   +1 more source

Developing evidence‐based, cost‐effective P4 cancer medicine for driving innovation in prevention, therapeutics, patient care and reducing healthcare inequalities

Molecular Oncology, EarlyView.
The cancer problem is increasing globally with projections up to the year 2050 showing unfavourable outcomes in terms of incidence and cancer‐related deaths. The main challenges are prevention, improved therapeutics resulting in increased cure rates and enhanced health‐related quality of life.
Ulrik Ringborg, Joachim von Braun, Julio Celis, Anton Berns, Michael Baumann, Tit Albreht, Nancy Abou‐Zeid, Vanderlei Bagnato, Christian Brandts, Chien‐Jen Chen, Massimiliano di Pietro, Manjit Dosanjh, Thomas Dubois, Alexander Eggermont, Angelika Eggert, Ingemar Ernberg, Sara Faithfull, Johannes Förner, Stefan Fröhling, Manuel Heitor, Leroy Hood, Wei Jiang, Bengt Jönsson, Ravi Kannan, Maria Leptin, Su Li, Peter Lindgren, Douglas Lowy, Jun Ma, Alex Markham, Péter Nagy, Simon Oberst, M. Iqbal Parker, Danielle Rodin, Kevin Ryan, Joachim Schüz, Richard Sullivan, Josep Tabernero, Peter Turkson, Oliver Várhelyi, Harold Varmus, Chijie Wang, Elisabete Weiderpass, Nils Wilking   +43 more
wiley   +1 more source

Ideating Explainable AI

, 2023
Exploring user's mental models of an AI-driven recruitment system using design-thinking methods as an approach to ideating XAI.
Sheridan, Helen, Murphy, Emma, O'Sullivan, Dympna   +2 more
openaire   +3 more sources

Dammarenediol II enhances etoposide‐induced apoptosis by targeting O‐GlcNAc transferase and Akt/GSK3β/mTOR signaling in liver cancer

Molecular Oncology, EarlyView.
Etoposide induces DNA damage, activating p53‐dependent apoptosis via caspase‐3/7, which cleaves PARP1. Dammarenediol II enhances this apoptotic pathway by suppressing O‐GlcNAc transferase activity, further decreasing O‐GlcNAcylation. The reduction in O‐GlcNAc levels boosts p53‐driven apoptosis and influences the Akt/GSK3β/mTOR signaling pathway ...
Jaehoon Lee, Byung‐Cheol Han, Gi‐Bang Koo, Jihye Park, Mijin Kwon, Young Bin Park, Jae‐Mun Choi, Seung‐Ho Lee, Sangho Roh   +8 more
wiley   +1 more source

How artificial intelligence reduces human bias in diagnostics?

AIMS Bioengineering
Accurate diagnostics of neurological disorders often rely on behavioral assessments, yet traditional methods rooted in manual observations and scoring are labor-intensive, subjective, and prone to human bias.
Artur Luczak
doaj   +1 more source

Explainable AI for Industry 5.0: Vision, Architecture, and Potential Directions

IEEE Open Journal of Industry Applications
The Industrial Revolution has shifted toward Industry 5.0, reinventing the Industry 4.0 operational process by introducing human elements into critical decision processes.
Chandan Trivedi, Pronaya Bhattacharya, Vivek Kumar Prasad, Viraj Patel, Arunendra Singh, Sudeep Tanwar, Ravi Sharma, Srinivas Aluvala, Giovanni Pau, Gulshan Sharma   +9 more
semanticscholar   +1 more source