Advanced Deep Learning and Hybrid Architectures in Biomedical Data Analysis for Advances in Medicine
This review summarizes AI methods for biomedical imaging and clinical data analysis. Deep learning and multimodal models improve feature learning and diagnostic accuracy. Future progress requires explainable and generalizable AI for precision medicine.
Lifeng Li +4 more
wiley +1 more source
Detection of UDP-Based Volumetric DDoS Attacks in IoT Environments Using LSTM with Temporal Attention Mechanism. [PDF]
Aydin BE, Güney Z, Aydin H.
europepmc +1 more source
This article illustrates the current dilemmas of myocardial infarction patients after traditional cardiac rehabilitation, as well as the feasibility of using artificial intelligence to optimize and assist with rehabilitation programs such as by integrating mobile apps, wearables, ECGs, medication, vital signs, and assessment data; finally, the AI ...
Xinyuan Huang +6 more
wiley +1 more source
Passive Screening for Depressive Symptoms Using Daily Wrist Actigraphy and Deep Learning: Model Development and Validation Study. [PDF]
Enkhbayar D +5 more
europepmc +1 more source
Prediction of Failure in Lithium‐Rich Cathode Half‐Cells Using Early‐Cycle Data
Using a dataset constructed from the performance evolution of Li‐rich cathode materials, a GBDT‐based model was developed for early half‐cell failure prediction. By using only data from the first 50 cycles, the model enables rapid identification of failure tendencies and provides an efficient tool for performance screening and evaluation.
Xiaoya Zhang +6 more
wiley +1 more source
A Gear-Driven Plantar Energy Harvester with Integrated Self-Sensing for Human Locomotion Recognition. [PDF]
Wang X +6 more
europepmc +1 more source
Fault Detection of Electric Motors via Symmetrized Dot Pattern‐Based Features
ABSTRACT This study proposes a novel symmetrized dot pattern (SDP) approach using designed SDP‐based features, extracted from transformed vibration signals, for fault detection. These features describe the compactness, inclination, and shape of the “snowflake” diagram distributions.
Mario Spirto +6 more
wiley +1 more source
Hybrid computational intelligence framework for accurate wind power forecasting and grid integration applications. [PDF]
Alkhrissat T +7 more
europepmc +1 more source
ABSTRACT Conventional fault‐diagnosis methods, largely grounded in one‐dimensional signal analysis and linear modeling, often fail to detect complex nonlinear faults in rotating machinery operating under variable loads. Data‐driven approaches also face challenges in extracting discriminative information from high‐dimensional multisensor measurements ...
Amirreza Marzband, Javad Poshtan
wiley +1 more source
Enhancing COVID-19 Forecasting Accuracy in Malaysia Using a Hybrid ARIMA-LSTM Model With Exogenous Variables: A Time-Series Predictive Study. [PDF]
Mahmud A +4 more
europepmc +1 more source

