Search Results - Computing methodologies Machine learning Learning settings Learning from demonstrations

Facial and Gesture Recognition-based Deep Learning Model for Academic Time Attendance at PKRU Demonstration School

Authors: Tanagrit Chansaeng Pita Jarupunphol

Source: Artificial Intelligence and Applications.

Speech pattern disorders in verbally fluent individuals with autism spectrum disorder: a machine learning analysis.

Authors: Hu, Chuanbo Thrasher, Jacob Li, Wenqi et al.

Source: Frontiers in Neuroinformatics; 2025, p1-13, 13p

Subject Terms: AUTISM spectrum disorders, MACHINE learning, VOICE analysis, EVALUATION methodology, SPEECH disorders, SUPPORT vector machines, PROSODIC analysis (Linguistics), PHONETICS

Do Children with Autism Spectrum Disorders (ASD) Have Deep Learning Ability? An Exploratory Research in Inclusive Play.

Authors: Zhu, Yanrong Su, Xueyun

Source: Journal of Intelligence; Nov2025, Vol. 13 Issue 11, p135, 22p

Subject Terms: AUTISM spectrum disorders, LEARNING ability, PRESCHOOL children, EMOTIONAL experience, BEHAVIORAL assessment, SOCIAL contact

Geographic Terms: CHINA

Integration of deep learning, big data and biomechanics to optimize the layout of new railroad energy bioeffects.

Authors: Xiao, Yanfeng

Source: Molecular & Cellular Biomechanics; 2025, Vol. 22 Issue 4, p1-15, 15p

Subject Terms: DEEP learning, BIG data, BIOMECHANICS, ARTIFICIAL neural networks, ENVIRONMENTAL impact analysis, ENERGY consumption, SUSTAINABLE development, INFRASTRUCTURE (Economics)

Enhancing Typhoid Fever Diagnosis Based on Clinical Data Using a Lightweight Machine Learning Metamodel.

Authors: Nishat, Fariha Ahmed Mridha, M. F. Mahmud, Istiak et al.

Source: Diagnostics (2075-4418); Mar2025, Vol. 15 Issue 5, p562, 25p

Subject Terms: ENSEMBLE learning, TYPHOID fever, RECEIVER operating characteristic curves, MACHINE learning, RESOURCE-limited settings

Challenges in the Clinical Application of Machine Learning for Pancreatic Cancer.

Authors: Večurkovská, Ivana Roškovičová, Veronika Kaťuchová, Jana

Source: Bratislava Medical Journal / Bratislavské Lekárske Listy; Oct2025, Vol. 126 Issue 10, p2437-2450, 14p

Subject Terms: MACHINE learning, PANCREATIC cancer, MODEL validation, CLINICAL medicine, HETEROGENEITY, ETHICAL problems, INDIVIDUALIZED medicine, DIAGNOSIS

Prognostic Factors for Mortality Following Diaphragmatic Herniorrhaphy in Dogs and Cats: Multivariable Logistic Regression and Machine Learning Approaches.

Authors: Kwananocha, Irin Niyom, Sirirat Budsayaplakorn, Pharkpoom et al.

Source: Veterinary Sciences. Sep2025, Vol. 12 Issue 9, p819. 18p.

Outlier Detection in Hydrological Data Using Machine Learning: A Case Study in Lao PDR.

Authors: Kim, Chung-Soo Kim, Cho-Rong Kok, Kah-Hoong

Source: Water (20734441); Nov2025, Vol. 17 Issue 21, p3120, 28p

Subject Terms: OUTLIER detection, MACHINE learning, WATER management, ENSEMBLE learning, HYDROLOGICAL databases, FLOOD forecasting

Geographic Terms: LAOS

Exploration of 3D Few-Shot Learning Techniques for Classification of Knee Joint Injuries on MR Images.

Authors: Dang, Vinh Hiep Nguyen, Minh Tri Le, Ngoc Hoang et al.

Source: Diagnostics (2075-4418); Jul2025, Vol. 15 Issue 14, p1808, 15p

Subject Terms: KNEE injuries, MAGNETIC resonance imaging, COMPUTER-assisted image analysis (Medicine), MACHINE learning, CLASSIFICATION algorithms, COMPUTER-aided diagnosis, LEARNING

EyeInvaS: Lowering Barriers to Public Participation in Invasive Alien Species Monitoring Through Deep Learning.

Authors: Chen, Hao Zhou, Jiaogen Wu, Wenbiao et al.

Source: Animals (2076-2615); Nov2025, Vol. 15 Issue 21, p3181, 16p

Subject Terms: DEEP learning, IMAGE recognition (Computer vision), CITIZEN science, INTRODUCED species, PARTICIPATION, ENVIRONMENTAL protection, BIODIVERSITY, SCIENTIFIC observation

Geographic Terms: CHINA

Predicting weaning weight in Hair goat kids: a comparative analysis of tree-based machine learning approaches using environmental and herd data.

Authors: Esener, Necati Kal, Yavuz

Source: Animal Production Science. 2025, Vol. 65 Issue 9, p1-12. 12p.

The Role of Artificial Intelligence in Bathing Water Quality Assessment: Trends, Challenges, and Opportunities.

Authors: Khan, M Usman Saeed Battamo, Ashenafi Yohannes Ravindar, Rajendran et al.

Source: Water (20734441); Nov2025, Vol. 17 Issue 21, p3176, 32p

Subject Terms: ARTIFICIAL intelligence, WATER quality, PREDICTION models, MACHINE learning, REMOTE sensing devices, ENVIRONMENTAL monitoring, PUBLIC health, DATA integration

Deep Learning Network with Illuminant Augmentation for Diabetic Retinopathy Segmentation Using Comprehensive Anatomical Context Integration.

Authors: Chankhachon, Sakon Kansomkeat, Supaporn Bhurayanontachai, Patama et al.

Source: Diagnostics (2075-4418); Nov2025, Vol. 17 Issue 21, p2762, 32p

Subject Terms: DIABETIC retinopathy, IMAGE segmentation, COMPUTER-assisted image analysis (Medicine), FALSE positive error, DATA augmentation, DEEP learning, TRANSFORMER models, ANATOMICAL variation

Deep Learning With DAGs.

Authors: Balgi, Sourabh Daoud, Adel Peña, Jose M. et al.

Source: Sociological Methods & Research; Nov2025, Vol. 54 Issue 4, p1624-1682, 59p

Subject Terms: DEEP learning, CAUSAL inference, CAUSATION (Philosophy), CAUSAL models, DIRECTED acyclic graphs, STATUS attainment, SCIENTIFIC observation, FLOWGRAPHS

Predicting the Higher Energy Need for Effective Defibrillation Using Machine Learning Based on an Animal Model.

Authors: Pál-Jakab, Ádám Kiss, Boldizsár Nagy, Bettina et al.

Source: Journal of Clinical Medicine; Jun2025, Vol. 14 Issue 11, p3879, 18p

Subject Terms: STATISTICAL significance, VENTRICULAR fibrillation, MACHINE learning, VENTRICULAR tachycardia, INTENSIVE care units

Diagnostic Accuracy of Deep Learning for Intracranial Hemorrhage Detection in Non-Contrast Brain CT Scans: A Systematic Review and Meta-Analysis.

Authors: Karamian, Armin Seifi, Ali

Source: Journal of Clinical Medicine; Apr2025, Vol. 14 Issue 7, p2377, 27p

Subject Terms: RANDOM effects model, INTRACRANIAL hemorrhage, ARTIFICIAL intelligence, DEEP learning, COMPUTED tomography

Personalized rTMS treatment recommendation with retrieval-augmented LLM reasoning.

Authors: Xu, Lingling Xie, Haoran Tao, Xiaohui et al.

Source: Brain Informatics; 11/7/2025, Vol. 12 Issue 1, p1-12, 12p

Subject Terms: TRANSCRANIAL magnetic stimulation, INDIVIDUALIZED medicine, MENTAL depression, MACHINE learning, MEDICAL protocols, NEUROMODULATION, LANGUAGE models

Application of Artificial Intelligence in Hydrological Modeling for Streamflow Prediction in Ungauged Watersheds: A Review.

Authors: Gacu, Jerome G. Monjardin, Cris Edward F. Mangulabnan, Ronald Gabriel T. et al.

Source: Water (20734441); Sep2025, Vol. 17 Issue 18, p2722, 37p

Subject Terms: ARTIFICIAL intelligence, STREAMFLOW, HYDROLOGIC models, DEEP learning, REMOTE sensing devices, WATERSHEDS, MACHINE learning, INFERENTIAL statistics

Socializing AI: Integrating Social Network Analysis and Deep Learning for Precision Dairy Cow Monitoring—A Critical Review.

Authors: Parivendan, Sibi Chakravathy Sailunaz, Kashfia Neethirajan, Suresh

Source: Animals (2076-2615); Jul2025, Vol. 15 Issue 13, p1835, 48p

Subject Terms: ARTIFICIAL intelligence, DEEP learning, ETHICAL problems, PRECISION farming, DAIRY cattle, SOCIAL network analysis, ANIMAL welfare, SCIENTIFIC observation

Smart feature extraction using deep learning for early diagnosis of chronic diseases in next-generation medical decision support systems.

Authors: Ahmed, Yazeed K. Naji, Abdallah N. A.

Source: Network Modeling & Analysis in Health Informatics & Bioinformatics; 11/11/2025, Vol. 14 Issue 1, p1-20, 20p