Recent advances in deep learning models: a systematic literature review
In recent years, deep learning has evolved as a rapidly growing and stimulating field of
machine learning and has redefined state-of-the-art performances in a variety of …
machine learning and has redefined state-of-the-art performances in a variety of …
Develo** deep transfer and machine learning models of chest X-ray for diagnosing COVID-19 cases using probabilistic single-valued neutrosophic hesitant fuzzy
This study presents a novel dynamic localisation-based decision (DLBD) with fuzzy
weighting with zero inconsistency (FWZIC) under a probabilistic single-valued neutrosophic …
weighting with zero inconsistency (FWZIC) under a probabilistic single-valued neutrosophic …
Optimization of cnn using modified honey badger algorithm for sleep apnea detection
Sleep Apnea (SA) is the most prevalent breathing sleep problem, and if left untreated, it can
lead to catastrophic neurological and cardiovascular illnesses. Conventionally …
lead to catastrophic neurological and cardiovascular illnesses. Conventionally …
Recent Advances of Chimp Optimization Algorithm: Variants and Applications
Abstract Chimp Optimization Algorithm (ChOA) is one of the recent metaheuristics swarm
intelligence methods. It has been widely tailored for a wide variety of optimization problems …
intelligence methods. It has been widely tailored for a wide variety of optimization problems …
Enhancing robot path planning through a twin-reinforced chimp optimization algorithm and evolutionary programming algorithm
The importance of efficient path planning (PP) cannot be overstated in the domain of robots,
as it involves the utilization of intelligent algorithms to determine the optimal trajectory for …
as it involves the utilization of intelligent algorithms to determine the optimal trajectory for …
Stability Analysis, Modulation Instability, and Beta-Time Fractional Exact Soliton Solutions to the Van der Waals Equation.
The study consists of the distinct types of the exact soliton solutions to an important model
called the beta-time fractional (1+ 1)-dimensional non-linear Van der Waals equation. This …
called the beta-time fractional (1+ 1)-dimensional non-linear Van der Waals equation. This …
Optimized Xception Learning Model and XgBoost Classifier for Detection of Multiclass Chest Disease from X-ray Images
Computed tomography (CT) scans, or radiographic images, were used to aid in the early
diagnosis of patients and detect normal and abnormal lung function in the human chest …
diagnosis of patients and detect normal and abnormal lung function in the human chest …
User preference interaction fusion and swap attention graph neural network for recommender system
Recommender systems are widely used in various applications. Knowledge graphs are
increasingly used to improve recommendation performance by extracting valuable …
increasingly used to improve recommendation performance by extracting valuable …
Development and external validation of an interpretable machine learning model for the prediction of intubation in the intensive care unit
J Liu, X Duan, M Duan, Y Jiang, W Mao, L Wang… - Scientific Reports, 2024 - nature.com
Given the limited capacity to accurately determine the necessity for intubation in intensive
care unit settings, this study aimed to develop and externally validate an interpretable …
care unit settings, this study aimed to develop and externally validate an interpretable …
Multivariate time series short term forecasting using cumulative data of coronavirus
Coronavirus emerged as a highly contagious, pathogenic virus that severely affects the
respiratory system of humans. The epidemic-related data is collected regularly, which …
respiratory system of humans. The epidemic-related data is collected regularly, which …