Results 61 to 70 of about 35,242 (295)

The effectiveness of explainable AI on human factors in trust models

Scientific Reports
Explainable AI has garnered significant traction in science communication research. Prior empirical studies have firmly established that explainable AI communication could improve trust in AI and that trust in AI engineers was argued to be an under ...
Justin C. Cheung, Shirley S. Ho
doaj   +1 more source

Implications of causality in artificial intelligence

Frontiers in Artificial Intelligence
Over the last decade, investment in artificial intelligence (AI) has grown significantly, driven by technology companies and the demand for PhDs in AI. However, new challenges have emerged, such as the ‘black box’ and bias in AI models.
Luís Cavique
doaj   +1 more source

Medically-oriented design for explainable AI for stress prediction from physiological measurements

BMC Medical Informatics and Decision Making, 2022
Background In the last decade, a lot of attention has been given to develop artificial intelligence (AI) solutions for mental health using machine learning.
Dalia Jaber, Hazem Hajj, Fadi Maalouf, Wassim El-Hajj   +3 more
doaj   +1 more source

Metastasis on pause: How dormant tumor cells stay hidden within the tumor microenvironment and evade immune surveillance

Molecular Oncology, EarlyView.
Dormant cancer cells can hide in distant organs for years, evading treatment and the immune system. This review highlights how signals from the surrounding tissue and immune environment keep these cells inactive or trigger their reawakening. Understanding these mechanisms may help develop therapies to eliminate or control dormant cells and prevent ...
Kanishka Tiwary, Jose Javier Bravo‐Cordero   +1 more
wiley   +1 more source

Explainable AI: The New 42? [PDF]

, 2018
Explainable AI is not a new field. Since at least the early exploitation of C.S. Pierce’s abductive reasoning in expert systems of the 1980s, there were reasoning architectures to support an explanation function for complex AI systems, including applications in medical diagnosis, complex multi-component design, and reasoning about the real world.
Randy Goebel, Ajay Chander, Katharina Holzinger, Freddy Lécué, Zeynep Akata, Simone Stumpf, Peter Kieseberg, Andreas Holzinger   +7 more
openaire   +3 more sources

Explainable & Safe Artificial Intelligence in Radiology

Journal of the Korean Society of Radiology
Artificial intelligence (AI) is transforming radiology with improved diagnostic accuracy and efficiency, but prediction uncertainty remains a critical challenge.
Synho Do
doaj   +1 more source

Bringing Artificial Intelligence Literacy Into Online Education: Machine-Learning Integration Through Geometry in K–12 Teacher Professional Development

International Review of Research in Open and Distributed Learning
This study examined an online professional development program integrating artificial intelligence (AI) literacy into mathematics instruction through unplugged, explainable machine-learning activities.
Woonhee Sung, Yasemin Gunpinar
doaj   +1 more source

Stimulator of interferon genes agonist augmented antitumor immunity of osimertinib in Egfr‐mutated lung cancer

Molecular Oncology, EarlyView.
Combining osimertinib with the STING agonist ADU‐S100 activates innate and adaptive immunity to overcome the non‐inflamed microenvironment of Egfr‐mutant lung cancer. This combination increases NK and CD8+ T‐cell infiltration, associated with activation of the STING‐IRF3 pathway and local immunogenic cell death.
Jun Nishimura, Tadahiro Kuribayashi, Johannes Brägelmann, Sachi Okawa, Masataka Taoka, Shunta Mori, Tomoka Nishimura, Takaaki Tanaka, Go Makimoto, Kiichiro Ninomiya, Kammei Rai, Eiki Ichihara, Ryohei Katayama, Katsuyuki Hotta, Masahiro Tabata, Yosuke Togashi, Yoshinobu Maeda, Martin L. Sos, Katsuyuki Kiura, Kadoaki Ohashi   +19 more
wiley   +1 more source

Informing Design and Research Concerning Conversationally Explainable AI Systems by Collecting and Distilling Human Explanatory Dialogues

Information
Research into conversationally explainable artificial intelligence (CXAI) aims to emulate the interactive and co-constructive nature of explanations. From the perspective of human-centredness, previous work has shown that AI users prefer conversational ...
Alexander Berman, Christine Howes
doaj   +1 more source

PAK1 activation drives divergent resistance mechanisms to aromatase inhibition and tamoxifen in a luminal: A breast cancer model

Molecular Oncology, EarlyView.
Breast cancer remains a major cause of cancer death in women, frequently developing endocrine therapy resistance. This study demonstrates that upregulated p21‐activated kinase 1 (PAK1) activity drives resistance to tamoxifen and long‐term estrogen deprivation in ER+ breast cancer models.
Luisa Schwarzmüller, Janina Müller, Efstathios‐Iason Vlachavas, Lukas Beumers, Lena Fleischhacker, Sara Burmester, Angelika Wörner, Sabine Karolus, Dominic Helm, Cindy Körner, Stefan Wiemann   +10 more
wiley   +1 more source