Results 101 to 110 of about 19,632 (257)

Semi‐mechanistic population PK/PD model to aid clinical understanding of myelodysplastic syndromes following treatment with Venetoclax and Azacitidine

CPT: Pharmacometrics &Systems Pharmacology, Volume 14, Issue 3, Page 448-459, March 2025.
Abstract Myelodysplastic syndromes (MDS) represent a group of bone marrow disorders involving cytopenias, hypercellular bone marrow, and dysplastic hematopoietic progenitors. MDS remains a challenge to treat due to the complex interplay between disease‐induced and treatment‐related cytopenias.
Neha Thakre, Corinna Maier, Jiuhong Zha, Benjamin Engelhardt, Johannes E. Wolff, Sven Mensing   +5 more
wiley   +1 more source

Mechanistic Learning for Predicting Survival Outcomes in Head and Neck Squamous Cell Carcinoma

CPT: Pharmacometrics &Systems Pharmacology, Volume 14, Issue 3, Page 540-550, March 2025.
ABSTRACT We employed a mechanistic learning approach, integrating on‐treatment tumor kinetics (TK) modeling with various machine learning (ML) models to address the challenge of predicting post‐progression survival (PPS)—the duration from the time of documented disease progression to death—and overall survival (OS) in Head and Neck Squamous Cell ...
Kevin Atsou, Anne Auperin, Jôel Guigay, Sébastien Salas, Sebastien Benzekry   +4 more
wiley   +1 more source

Brown–Proschan Repair Policy for Repairable Systems Using the Discrete Weibull Failure Distribution and Markov Chains

Quality and Reliability Engineering International, EarlyView.
ABSTRACT A repairable system operates under a maintenance strategy involving scheduled preventive maintenance (PM) and corrective repair actions following failures. This study develops an exact analytical methodology using Markov chains with discrete states and time to calculate the expected number of failures E[N(t)]$\mathop {\mathbb {E}}[N(t)]$ under
Danilo G. O. Valadares, Roberto C. Quinino, Linda L. Ho, Frederico R. B. Cruz   +3 more
wiley   +1 more source

Distributed Mode-Dependent Event-Triggered Passive Filtering for Flexible Manipulator with Semi-Markov Parameters. [PDF]

Sensors (Basel), 2021
Ji Y, Zheng S.
europepmc   +1 more source

Integrating Image Segmentation and Deep Learning to Improve Radio Frequency Propagation Models

International Journal of Satellite Communications and Networking, EarlyView.
ABSTRACT This paper proposes a multi‐sensor approach to improve radio frequency (RF) propagation models, which play a key role in the rapidly expanding field of connected vehicle technology. Focusing on the 1‐ to 20‐GHz frequency range, which is critical for both satellite‐to‐vehicle and base station‐to‐vehicle communications, our study introduces a ...
Jonathan Israel, Xavier Boulanger, Vegard Arneson   +2 more
wiley   +1 more source

Network Latency Estimation for Telesurgery Using Deep Reinforcement Learning

SmartBot, EarlyView.
Overview of the proposed two‐stage deep reinforcement learning framework for network latency prediction in telesurgery. The pipeline includes data collection from simulated catheter navigation sessions (Philippines–Botswana), feature engineering, DQN‐based direction prediction (85.8% accuracy), direction‐to‐value transformation, and value forecasting ...
Bakang Kgopolo, Rodrigo S. Jamisola Jr., Molaletsa Namoshe   +2 more
wiley   +1 more source

On Semi-Markov and Semiregenerative Processes II

The Annals of Probability, 1978
An ergodic theorem is given for the age process $(I(t), Z(t))$ associated with a (possibly transient) semi-Markov chain $(I_n, X_n)^\infty_{n=0}$ whose sojourn times are not exclusively integer valued. Asymptotically the Markov part $(I(t):$ the state occupied at time $t)$ and the renewal part $(Z(t):$ the age in $I(t)$ at time $t)$ split into ...
openaire   +4 more sources

Comparison of fuzzy semi-Markov models for one unit with mixed standby units with and without preventive maintenance using regenerative point method. [PDF]

Heliyon, 2021
Temraz NSY.
europepmc   +1 more source

Artificial intelligence empowers targeted protein degradation: Core technological innovations, multi‐scenario applications, and translational prospects

Smart Molecules, EarlyView.
AI is transforming TPD by improving the design, prediction, and optimization of degraders such as PROTACs, molecular glues, and LYTACs. This review summarizes key AI‐driven advances, highlights applications across drug discovery stages, and discusses remaining challenges and future directions for accelerating the development of therapies against ...
Shuanglin Qin, Rui Peng, Guangshuai Zhang, Si Yan, Jin Xiao, Zishu Liu, Ziyu Tan, Qingqing Xie, Shangjie Li, Wei Luo, Xiaohe Xiao   +10 more
wiley   +1 more source

DQN‐Guided Subset‐Induced OCSVM Kernel Approximation for Imbalanced Anomaly Detection

IEEJ Transactions on Electrical and Electronic Engineering, EarlyView.
Anomaly detection under limited normal data remains a fundamental challenge due to severe class imbalance and scarcity of anomalies. We propose a novel framework that reformulates support vector selection in One‐Class SVM as a sequential decision‐making problem.
Wenqian Yu, Jiaying Wu, Jinglu Hu
wiley   +1 more source