Care of terminally ill / Palliative care

Investigating feature-engineered predictors for systolic blood pressure changes in an mHealth-based disease management program.

Mobile health (mHealth)-based disease management programs enable continuous monitoring of blood pressure (BP) and related health behaviors. Feature engineering may help to extract informative predictors from longitudinal data, potentially improving BP change prediction. This study aimed to evaluate whether feature-engineered predictors can improve the prediction of systolic BP (SBP) changes using ...

An end-to-end convolutional neural network for secure image transmission via joint encryption and steganography.

Further attachment of image-based communication speed to sensitive areas must be provided with confidential and safe transmission. Conventional methods use encryption and steganography as distinct methods, hence producing either conspicuous artifacts (encryption) or attack vulnerability (steganography). Though cryptographic algorithms, including AES and DES, offer a high level of mathematical secu...

An Adaptive Blockchain Framework for Federated IoMT with Reinforcement Learning-Based Consensus and Resource Forecasting.

The rapid growth of the Internet of Medical Things (IoMT) has increased the adoption of remote healthcare applications and telemedicine services. A Ma...

Multi-view graph clustering via dual attention fusion and collaborative optimization.

Multi-view graph clustering, a fundamental task in data mining and machine learning, aims to partition nodes into disjoint groups by leveraging comple...

Perceived Potential and Challenges of Supporting Coronary Artery Disease Treatment Decisions With AI: Qualitative Study.

BACKGROUND: Coronary revascularization decision-making for patients with coronary artery disease (CAD) can be complex and challenging. Artificial inte...

Interpretable Machine Learning Model Using Digitized US Features for Classifying Complex Thyroid Nodules.

Purpose To develop a digitized integrated feature-based interpretable machine learning classification model to accurately recognize complex thyroid no...

Risk stratification in diabetic kidney disease: a review of prediction models for methodological advances and clinical application.

BACKGROUND: Diabetic kidney disease (DKD) represents the leading cause of end-stage renal disease (ESRD) worldwide, characterized by a complex pathoph...

Full-Scope Vectorization of Geographical Elements from Large-Size Remote Sensing Imagery.

Large-size very-high-resolution (VHR) remote sensing imagery has emerged as a critical data source for high-precision vector mapping of multi-scale ge...

Developing a Multimodal Screening Algorithm for Mild Cognitive Impairment and Early Dementia in Home Health Care: Protocol for a Cross-Sectional Case-Control Study Using Speech Analysis, Large Language Models, and Electronic Health Records.

BACKGROUND: Mild cognitive impairment and early dementia (MCI-ED) are frequently unrecognized in routine care, particularly in home health care (HHC),...

A Deep Learning-Based Human-Robot Collaborative Navigation Framework for Vascular Interventional Surgery.

BACKGROUND: Autonomous robotic surgery has demonstrated its potential for the optimal outcomes. However, vascular interventional surgery (VIS) with fl...

Interpretable model-driven end-to-end deep learning of geometric shaping for DML-based IM/DD systems.

Direct modulation lasers (DMLs) are a low-cost technology for short-reach intensity modulation and direct detection (IM/DD) systems due to their small...

Machine Learning Based Prediction of Tibial Insert Thickness in Total Knee Arthroplasty From Intraoperative Knee Joint Laxity Data.

Total knee arthroplasty (TKA) represents the gold standard for relieving pain and restoring function in patients with end-stage knee osteoarthritis. S...

SLPM: a lightweight deep learning model for end-to-end paper ECG digitization.

OBJECTIVE: The digitization of paper electrocardiograms (ECGs) faces several challenges, including amplified errors during segmentation and signal ext...

Mapping at-risk transportation infrastructure assets using statistical and machine learning methods.

Geotechnical assets such as highway embankments and slopes (HWS) are critical to the integrity of transportation infrastructure. However, they are lar...

DMPFDet: An end-to-end deformable mutual-promotion learning network for multispectral visible-infrared fusion detection.

Multimodal image fusion and object detection significantly enhance detection accuracy and robustness in complex environments, which is crucial for aut...

Radiomics analysis of early pregnancy ultrasound images to predict viability at the end of first trimester.

To determine whether there are radiomic ultrasound features of early pregnancy when viability is unknown, which in combination with clinical features,...

Integrated CT pipeline for automatic intracranial hemorrhage evaluation with GPT-enhanced clinical decision support.

OBJECTIVES: Intracranial hemorrhage (ICH) is a time-critical neurological emergency in which rapid CT-based assessment directly informs treatment deci...

Hybrid U-net-INR network for high precision sparse electromagnetic map reconstruction.

Sparse sampling hinders high-precision electromagnetic environment map reconstruction, crucial for spectrum management and situation awareness. To ove...

IUGC: A benchmark of landmark detection in end-to-end intrapartum ultrasound biometry.

Accurate intrapartum biometry plays a crucial role in monitoring labor progression and preventing complications. However, its clinical application is ...

LMSA-net: a lightweight multi-scale attention network for eeg-based emotion recognition.

Electroencephalogram (EEG)-based emotion recognition holds great potential in affective computing, mental health assessment, and human-computer intera...