Results 61 to 70 of about 14,251,445 (242)

Integrating Reinforcement Learning With Explainable Artificial Intelligence for Real‐Time Clinical Decision Support in Dynamic Healthcare Environments

Advanced Intelligent Systems, EarlyView.
A hybrid Reinforcement Learning–Explainable AI framework integrates SHAP and LIME explanations directly into a Deep Q‐Network inference loop for real‐time ICU decision support. Trained on 18 142 mechanically ventilated stays from the eICU database, the system attains 93.0% decision accuracy, 20% fewer errors than RL alone, and a 91% clinician trust ...
Jannatul Ferdaus Disha, MD Faiaz Zaman Dehan, Kazi Md. Tanvir Anzum   +2 more
wiley   +1 more source

Estimating Components in Finite Mixtures and Hidden Markov Models [PDF]

When the unobservable Markov chain in a hidden Markov model is stationary the marginal distribution of the observations is a finite mixture with the number of terms equal to the number of the states of the Markov chain.
D.S. Poskitt, Jing Zhang
core  

Exploiting Edge Semantics in Job Shop Scheduling Problem With Heterogeneous Graph Transformers

Advanced Intelligent Systems, EarlyView.
A heterogeneous graph transformer (HGT) is introduced for reinforcement learning‐based job shop scheduling by explicitly distinguishing precedence and machine‐contention relations through edge‐type‐specific attention. The proposed framework learns richer scheduling representations, improves decision quality over homogeneous graph models, and highlights
Bulent Soykan, Fatih Kasimoglu
wiley   +1 more source

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

Advanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne, Haodong Yao, Liyuan Wu, Yihe Pang, Fazhi Qi, Lina Zhao   +5 more
wiley   +1 more source

A Rare RIPK3 Variant Enhances Necroptosis and Promotes Inflammation in a Still Disease–Like Autoinflammatory Syndrome

Arthritis &Rheumatology, EarlyView.
Objective Still disease represents a prototypical polygenic systemic autoinflammatory disease, characterized by recurrent systemic inflammation and dysregulation of innate immunity. Despite extensive clinical characterization, familial clustering Still disease remains unreported.
Longfang Chen, Qihua Dai, Yu Xiao, Jialin Dai, Mengyan Wang, Yuning Ma, Yujie Shen, Zhimo Xu, Jianfen Meng, Xia Chen, Da Yi, Yue Sun, Hui Shi, Honglei Liu, Xiaobing Cheng, Yutong Su, Junna Ye, Huihui Chi, Zhuochao Zhou, Tingting Liu, Jialin Teng, Chengde Yang, Jinchao Jia, Qiongyi Hu   +23 more
wiley   +1 more source

Kajian Model Hidden Markov untuk Menduga Volatilitas Indeks Harga Saham

, 2013
Volatility is a measure of uncertainty, which is useful for investor to plan a good investment strategy. The problem is that volatility is unobservable, and estimating volatility is not a trivial task.
Baist, Abdul
core  

Global distribution of avian plumage coloration and patterning: the relative influence of climate, ecology, and sexual selection

Ecography, EarlyView.
Animal coloration exhibits substantial biogeographic variation, reflecting complex adaptations to both abiotic and biotic environments. Although the evolutionary mechanisms underlying avian plumage coloration have been widely studied, geographic variation in plumage patterning has received far less attention.
Yuqing Han, Ying Zeng, Tien Ming Lee, Long Wang, Chen Zeng, Pengfei Fan, Çağan H. Şekercioğlu, Weini Huang, Yang Liu   +8 more
wiley   +1 more source

Tuberculosis Surveillance Using a Hidden Markov Model [PDF]

Iranian Journal of Public Health, 2012
Background: Routinely collected data from tuberculosis surveillance system can be used to investigate and monitor the irregularities and abrupt changes of the disease incidence.
A Rafei, E Pasha, R Jamshidi Orak
doaj   +1 more source

Hidden Semi Markov Models for Multiple Observation Sequences: The mhsmm Package for R [PDF]

This paper describes the R package mhsmm which implements estimation and prediction methods for hidden Markov and semi-Markov models for multiple observation sequences. Such techniques are of interest when observed data is thought to be dependent on some
Søren Højsgaard, Jared O'Connell
core  

Perfect posterior simulation for mixture and hidden Markov models [PDF]

, 2010
In this paper we present an application of the read-once coupling from the past algorithm to problems in Bayesian inference for latent statistical models.
Berthelsen, Kasper Klitgaard, Laird A. Breyer, Berthelsen, Kasper K., Kasper K. Berthelsen, Roberts, Gareth O., Breyer, Laird A., Gareth O. Roberts   +6 more
core   +1 more source