Care of terminally ill / Palliative care

Model interpretability on private-safe oriented student dropout prediction.

Student dropout is a significant social issue with extensive implications for individuals and society, including reduced employability and economic downturns, which, in turn, drastically influence social sustainable development. Identifying students at high risk of dropping out is a major challenge for sustainable education. While existing machine learning and deep learning models can effectively ...

Electric vehicle braking energy recovery control method integrating fuzzy control and improved firefly algorithm.

Braking energy recovery is crucial for improving the energy efficiency and extending the range of electric vehicles. If a large amount of braking energy is wasted, it will lead to problems such as reduced range and increased battery burden for electric vehicles. Therefore, an electric vehicle braking energy recovery control model that integrates fuzzy control algorithm with genetic firefly algorit...

Leveraging Extended Windows in End-to-End Deep Learning for Improved Continuous Myoelectric Locomotion Prediction.

Current surface electromyography (sEMG) methods for locomotion mode prediction face limitations in anticipatory capability due to computation delays a...

PULSE: A DL-Assisted Physics-Based Approach to the Inverse Problem of Electrocardiography.

This study introduces an innovative approach combining deep-learning techniques with classical physics-based electrocardiographic imaging (ECGI) metho...

Deep Learning for High Speed Optical Coherence Elastography With a Fiber Scanning Endoscope.

Tissue stiffness is related to soft tissue pathologies and can be assessed through palpation or via clinical imaging systems, e.g., ultrasound or magn...

Effects of Dietary Gamma-Aminobutyric Acid (GABA) Inclusion on Acute Temperature Stress Responses in Juvenile Olive Flounder ().

This study investigated the potential of dietary gamma-aminobutyric acid (GABA) inclusion to mitigate acute temperature stress impacting the physiolog...

Multitask Deep Learning Models of Combined Industrial Absorption, Distribution, Metabolism, and Excretion Datasets to Improve Generalization.

The optimization of absorption, distribution, metabolism, and excretion (ADME) profiles of compounds is critical to the drug discovery process. As suc...

BINDTI: A Bi-Directional Intention Network for Drug-Target Interaction Identification Based on Attention Mechanisms.

The identification of drug-target interactions (DTIs) is an essential step in drug discovery. In vitro experimental methods are expensive, laborious, ...

Learning Consistent Semantic Representation for Chest X-ray via Anatomical Localization in Self-Supervised Pre-Training.

Despite the similar global structures in Chest X-ray (CXR) images, the same anatomy exhibits varying appearances across images, including differences ...

Enhancing diagnosis prediction with adaptive disease representation learning.

Diagnosis prediction predicts which diseases a patient is most likely to suffer from in the future based on their historical electronic health records...

Prediction of zinc, cadmium, and arsenic in european soils using multi-end machine learning models.

Heavy metal contamination in soil is a major environmental and public health concern, especially in regions with substantial industrial and agricultur...

Transforming residential water end use analysis: unleashing insights from widespread low-resolution smart metering data.

Transforming smart meter data captured at low-resolution litre intervals of 15 to 60 mins into residential water end use data provides valuable insigh...

Learning from leading indicators to predict long-term dynamics of hourly electricity generation from multiple resources.

Electricity is generated through various resources and then flows between regions via a complex system (grid). Imbalances in electricity generation ca...

Artificial Intelligence in Commercial Industry: Serving the End-to-End Patient Experience Across the Digital Ecosystem.

The purpose of this article is to evaluate the application of artificial intelligence (AI) from the perspective of the orthopaedic industry with respe...

Research on Upper Limb Motion Intention Classification and Rehabilitation Robot Control Based on sEMG.

sEMG is a non-invasive biomedical engineering technique that can detect and record electrical signals generated by muscles, reflecting both motor inte...

End-To-End Deep Learning Explains Antimicrobial Resistance in Peak-Picking-Free MALDI-MS Data.

Mass spectrometry is used to determine infectious microbial species in thousands of clinical laboratories across the world. The vast amount of data al...

Use of Artificial Intelligence in Lower Gastrointestinal and Small Bowel Disorders: An Update Beyond Polyp Detection.

Machine learning and its specialized forms, such as Artificial Neural Networks and Convolutional Neural Networks, are increasingly being used for dete...

DO-GMA: An End-to-End Drug-Target Interaction Identification Framework with a Depthwise Overparameterized Convolutional Network and the Gated Multihead Attention Mechanism.

Identification of potential drug-target interactions (DTIs) is a crucial step in drug discovery and repurposing. Although deep learning effectively de...

Deep one-class probability learning for end-to-end image classification.

One-class learning has many application potentials in novelty, anomaly, and outlier detection systems. It aims to distinguish both positive and negati...

The Use of AI in Mental Health Services to Support Decision-Making: Scoping Review.

BACKGROUND: Recent advancements in artificial intelligence (AI) have changed the care processes in mental health, particularly in decision-making supp...