Results 31 to 40 of about 57,852 (256)

Clinical Applications of Machine Learning

Annals of Surgery Open
Objective:. This review introduces interpretable predictive machine learning approaches, natural language processing, image recognition, and reinforcement learning methodologies to familiarize end users. Background:.
Nadayca Mateussi, PhD, Michael P. Rogers, MD, Emily A. Grimsley, MD, Meagan Read, MD, Rajavi Parikh, DO, Ricardo Pietrobon, MD, PhD, Paul C. Kuo, MD   +6 more
doaj   +1 more source

Interpreting the Black Box: Interpretable Machine Learning and Systems Pharmacology in Small-Molecule Therapeutics

Pharmaceutics
Small-molecule drug development faces high attrition rates driven by complex pharmacokinetics and unforeseen toxicities. While deep learning offers high predictive accuracy, its opaque “black-box” nature hinders mechanistic transparency, clinical trust ...
Huan Zhang, Yangyang Wang, Jihan Wang, Hui Li   +3 more
doaj   +1 more source

Foreign direct investment and local interpretable model-agnostic explanations: a rational framework for FDI decision making [PDF]

Journal of Economics Finance and Administrative Science
Purpose – This study aims to examine foreign direct investment (FDI) factors and develops a rational framework for FDI inflow in Western European countries such as France, Germany, the Netherlands, Switzerland, Belgium and Austria.
Devesh Singh
doaj   +1 more source

Gut microbiome and aging—A dynamic interplay of microbes, metabolites, and the immune system

FEBS Letters, EarlyView.
Age‐dependent shifts in microbial communities engender shifts in microbial metabolite profiles. These in turn drive shifts in barrier surface permeability of the gut and brain and induce immune activation. When paired with preexisting age‐related chronic inflammation this increases the risk of neuroinflammation and neurodegenerative diseases.
Aaron Mehl, Eran Blacher
wiley   +1 more source

Interpretable Machine Learning of Two‐Photon Absorption

Advanced Science, 2023
Molecules with strong two‐photon absorption (TPA) are important in many advanced applications such as upconverted laser and photodynamic therapy, but their design is hampered by the high cost of experimental screening and accurate quantum chemical (QC ...
Yuming Su, Yiheng Dai, Yifan Zeng, Caiyun Wei, Yangtao Chen, Fuchun Ge, Peikun Zheng, Da Zhou, Pavlo O. Dral, Cheng Wang   +9 more
doaj   +1 more source

The human gut microbiome across the life course

FEBS Letters, EarlyView.
Despite significant individual variation and continuous change throughout life, the human gut microbiome follows some life stage‐specific trends. This article provides a brief overview of how gut microbiome composition shifts across different phases of life. Created in BioRender. Özkurt, E. (2026) https://BioRender.com/8q4nrnc.
Alise J. Ponsero, Basak Bahcivanci, Antonietta Hayhoe, Animesh Acharjee, Ezgi Özkurt   +4 more
wiley   +1 more source

SMILE: systems metabolomics using interpretable learning and evolution

BMC Bioinformatics, 2021
Background Direct link between metabolism and cell and organism phenotype in health and disease makes metabolomics, a high throughput study of small molecular metabolites, an essential methodology for understanding and diagnosing disease development and ...
Chengyuan Sha, Miroslava Cuperlovic-Culf, Ting Hu   +2 more
doaj   +1 more source

Modelling stem cell differentiation related processes—A practical overview for biologists

FEBS Letters, EarlyView.
Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar, Xinqi Yan, Lucas F. Jansen Klomp, Stefano Schivo, Janine N. Post   +4 more
wiley   +1 more source

Interpretable machine learning prediction of all-cause mortality

Communications Medicine, 2022
Qui et al. present a new approach, IMPACT, that uses explainable artificial intelligence to analyze all-cause mortality. IMPACT provides insights into the individualized mortality risk scores, while maintaining high model accuracy and the expressive ...
Wei Qiu, Hugh Chen, Ayse Berceste Dincer, Scott Lundberg, Matt Kaeberlein, Su-In Lee   +5 more
doaj   +1 more source

Conceptual challenges for interpretable machine learning [PDF]

Synthese, 2020
AbstractAs machine learning has gradually entered into ever more sectors of public and private life, there has been a growing demand for algorithmic explainability. How can we make the predictions of complex statistical models more intelligible to end users?
openaire   +3 more sources