Results 51 to 60 of about 634,036 (142)

A Two‐Stage Hybrid Feature Selection and Ensemble Learning Framework With Explainable AI for Accurate PCOS Prediction

open access: yesHealth Science Reports, Volume 9, Issue 9, September 2026.
ABSTRACT Background and Aims Polycystic ovary syndrome (PCOS) is the most prevalent endocrine ailment impacting women of reproductive age, distinguished by ongoing imbalances of hormones that lead to the growth of various ovarian cysts alongside other health issues.
Md. Rakibul Hasan Efty   +4 more
wiley   +1 more source

Multi‐Modal AI Approach in Depression Detection and Treatment: A Systematic Review of Last Decade

open access: yesWIREs Data Mining and Knowledge Discovery, Volume 16, Issue 3, September 2026.
Overview of multimodal approaches for depression detection and treatment. ABSTRACT Depression is a common and devastating mental health illness with serious personal and societal consequences. Despite advancing treatment techniques, there are still hurdles in the effective diagnosis and treatment of depression, such as prompt diagnosis, personalized ...
Smith K. Khare   +3 more
wiley   +1 more source

Molecular descriptor driven QSPR modeling of Papp, TEER and Efflux Ratio from Caco‐2 cells using machine learning for various phytochemicals

open access: yesJournal of the Science of Food and Agriculture, Volume 106, Issue 11, Page 6606-6616, 30 August 2026.
Abstract BACKGROUND The present study aimed to develop and validate quantitative structure–property relationship (QSPR) models for predicting permeability related bioavailability indicators including apparent permeability (Papp), trans‐epithelial electrical resistance (TEER) and efflux ratio (ER) based on molecular descriptors (n = 5003) of 83 ...
Jin‐Woo Kim   +5 more
wiley   +1 more source

Lidar‐Based Object Tracking of Traffic Participants with Sensor Nodes in Existing Urban Infrastructure

open access: yesAdvanced Intelligent Systems, Volume 8, Issue 8, August 2026.
This paper presents a lidar‐based sensor node design and a rule‐based state observer for edge‐based traffic participant tracking. Unlike other state‐of‐the‐art methods, this state observer enables real‐time, CPU‐only edge processing without relying on machine learning approaches.
Simon Schäfer   +2 more
wiley   +1 more source

Explainable Machine Learning With Hybrid Feature Selection for Thyroid Disease Classification: A Case Study in Bangladesh

open access: yesEngineering Reports, Volume 8, Issue 8, August 2026.
Our research establishes a hybrid feature selection and ensemble machine learning pipeline for the classification of euthyroid, hyperthyroid, hypothyroid, and subclinical hypo‐ and hyperthyroid disorders. Variance Threshold with Backward Feature Elimination attained nearly 100% accuracy, while SHAP and LIME clarified the significance of features and ...
Md. Minhajul Abedin   +5 more
wiley   +1 more source

Recursive Estimation in Econometrics [PDF]

open access: yes
An account is given of recursive regression and of Kalman filtering which gathers the important results and the ideas that lie behind them within a small compass. It emphasises the areas in which econometricians have made contributions, which include the
Stephen Pollock
core  

PReMo: an analyzer for Probabilistic Recursive Models [PDF]

open access: yes, 2007
This paper describes PReMo, a tool for analyzing Recursive Markov Chains, and their controlled/game extensions: (1-exit) Recursive Markov Decision Processes and Recursive Simple Stochastic ...
Dominik Wojtczak   +3 more
core  

Computation of the para-pseudoinverse for oversampled filter banks: Forward and backward Greville formulas [PDF]

open access: yes, 2008
This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2008 IEEE. Personal use of this material is permitted.
Cong Ling   +6 more
core   +1 more source

Understanding the Kalman Filter: an Object Oriented Programming Perspective. [PDF]

open access: yes
The basic ideals underlying the Kalman filter are outlined in this paper without direct recourse to the complex formulae normally associated with this method. The novel feature of the paper is its reliance on a new algebraic system based on the first two
Snyder, R.D., Forbes, C.S.
core  

Bayes, Neyman and Neyman-Bayes Inference for Queueing Systems [PDF]

open access: yes
In this paper we will use the Bayesian inference for the parameters that appear in the queueing systems. We will estimate these parameters and we will build confidence intervals and significance tests for them, considering the parameters of the ...
Ciuiu, Daniel
core  

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