Results 91 to 100 of about 24,804 (235)

Medical Knowledge Integration Into Reinforcement Learning Algorithms for Dynamic Treatment Regimes

open access: yesInternational Statistical Review, EarlyView.
Summary The goal of precision medicine is to provide individualised treatment at each stage of chronic diseases, a concept formalised by dynamic treatment regimes (DTR). These regimes adapt treatment strategies based on decision rules learned from clinical data to enhance therapeutic effectiveness.
Sophia Yazzourh   +3 more
wiley   +1 more source

Breeding 5.0: Artificial intelligence (AI)‐decoded germplasm for accelerated crop innovation

open access: yesJournal of Integrative Plant Biology, EarlyView.
ABSTRACT Crop breeding technologies are vital for global food security. While traditional methods have improved yield, stress tolerance, and nutrition, rising challenges such as climate instability, land loss, and pest pressure now demand new solutions.
Jiayi Fu   +4 more
wiley   +1 more source

Computational Tonality Estimation: Signal Processing and Hidden Markov Models [PDF]

open access: yes, 2009
PhDThis thesis investigates computational musical tonality estimation from an audio signal. We present a hidden Markov model (HMM) in which relationships between chords and keys are expressed as probabilities of emitting observable chords from a hidden
Noland, Katy C
core  

A perspective on automated rapid eye movement sleep assessment

open access: yesJournal of Sleep Research, Volume 34, Issue 2, April 2025.
Summary Rapid eye movement sleep is associated with distinct changes in various biomedical signals that can be easily captured during sleep, lending themselves to automated sleep staging using machine learning systems. Here, we provide a perspective on the critical characteristics of biomedical signals associated with rapid eye movement sleep and how ...
Mathias Baumert, Huy Phan
wiley   +1 more source

Regularized Urdu Speech Recognition with Semi-Supervised Deep Learning

open access: yesApplied Sciences, 2019
Automatic Speech Recognition, (ASR) has achieved the best results for English, with end-to-end neural network based supervised models. These supervised models need huge amounts of labeled speech data for good generalization, which can be quite a ...
Mohammad Ali Humayun   +6 more
doaj   +1 more source

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

open access: yes
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  

Artificially intelligent accompaniment using Hidden Markov Models to model musical structure [PDF]

open access: yes, 2008
Background in Music Performance and Accompaniment. Musical accompanists may not always be available during practice, or the available accompanist may not have the technical ability necessary.
Alan Smaill (16064372)   +3 more
core  

A semi-Markov model for stroke with piecewise-constant hazards in the presence of left, right and interval censoring. [PDF]

open access: yes, 2013
This paper presents a parametric method of fitting semi-Markov models with piecewise-constant hazards in the presence of left, right and interval censoring. We investigate transition intensities in a three-state illness-death model with no recovery.
Kapetanakis, V   +5 more
core   +1 more source

AI in chemical engineering: From promise to practice

open access: yesAIChE Journal, Volume 72, Issue 7, July 2026.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew   +4 more
wiley   +1 more source

Option pricing using hidden Markov models

open access: yes, 2006
Includes bibliographical references (leaves 144-149).This work will present an option pricing model that accommodates parameters that vary over time, whilst still retaining a closed-form expression for option prices: the Hidden Markov Option Pricing ...
Anderson, Michael
core  

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