Identifying and Reporting Dependent Adult abuse

SLAPP: Subgraph-level attention-based performance prediction for deep learning models.

The intricacy of the Deep Learning (DL) landscape, brimming with a variety of models, applications, and platforms, poses considerable challenges for the optimal design, optimization, or selection of suitable DL models. One promising avenue to address this challenge is the development of accurate performance prediction methods. However, existing methods reveal critical limitations. Operator-level m...

Image based prognosis in head and neck cancer using convolutional neural networks: a case study in reproducibility and optimization.

In the past decade, there has been a sharp increase in publications describing applications of convolutional neural networks (CNNs) in medical image analysis. However, recent reviews have warned of the lack of reproducibility of most such studies, which has impeded closer examination of the models and, in turn, their implementation in healthcare. On the other hand, the performance of these models ...

Content framing role on public sentiment formation for pre-crisis detection on sensitive issue via sentiment analysis and content analysis.

Social media has been tremendously used worldwide for a variety of purposes. Therefore, engagement activities such as comments have attracted many sch...

Identifying Potential Lyme Disease Cases Using Self-Reported Worldwide Tweets: Deep Learning Modeling Approach Enhanced With Sentimental Words Through Emojis.

BACKGROUND: Lyme disease is among the most reported tick-borne diseases worldwide, making it a major ongoing public health concern. An effective Lyme ...

Deep Learning-Based Automated Labeling of Coronary Segments for Structured Reporting of Coronary Computed Tomography Angiography in Accordance With Society of Cardiovascular Computed Tomography Guidelines.

PURPOSE: To evaluate a novel deep learning (DL)-based automated coronary labeling approach for structured reporting of coronary artery disease accordi...

Multi-Label Classification With Dual Tail-Node Augmentation for Drug Repositioning.

Due to the lengthy and costly process of new drug discovery, increasing attention has been paid to drug repositioning, i.e., identifying new drug-dise...

STTRE: A Spatio-Temporal Transformer with Relative Embeddings for multivariate time series forecasting.

The prevalence of multivariate time series data across several disciplines fosters a demand and, subsequently, significant growth in the research and ...

An Interventional Radiologist's Primer of Critical Appraisal of Artificial Intelligence Research.

Recent advances in artificial intelligence (AI) are expected to cause a significant paradigm shift in all digital data-driven aspects of information g...

Deep Learning Empowers the Discovery of Self-Assembling Peptides with Over 10 Trillion Sequences.

Self-assembling of peptides is essential for a variety of biological and medical applications. However, it is challenging to investigate the self-asse...

Self-reporting with checklists in artificial intelligence research on medical imaging: a systematic review based on citations of CLAIM.

OBJECTIVE: To evaluate the usage of a well-known and widely adopted checklist, Checklist for Artificial Intelligence in Medical imaging (CLAIM), for s...

Deep Learning Technology to Recognize American Sign Language Alphabet.

Historically, individuals with hearing impairments have faced neglect, lacking the necessary tools to facilitate effective communication. However, adv...

Ultrastretchable and highly conductive hydrogels based on Fe- lignin nanoparticles for subzero wearable strain sensor.

Conductive hydrogels have attracted considerable interest for potential applications in soft robotics, electronic skin and human monitoring. However, ...

Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Modeling Studies: Development and Validation.

BACKGROUND: The reporting of machine learning (ML) prognostic and diagnostic modeling studies is often inadequate, making it difficult to understand a...

Artificial intelligence for dementia research methods optimization.

Artificial intelligence (AI) and machine learning (ML) approaches are increasingly being used in dementia research. However, several methodological ch...

PEPNet: A barotropic primitive equations-based network for wind speed prediction.

In wind speed prediction technologies, deep learning-based methods have achieved promising advantages. However, most existing methods focus on learnin...

Investigating the impact of structured reporting on the linguistic standardization of radiology reports through natural language processing over a 10-year period.

OBJECTIVES: To investigate how a transition from free text to structured reporting affects reporting language with regard to standardization and disti...

Sparser spiking activity can be better: Feature Refine-and-Mask spiking neural network for event-based visual recognition.

Event-based visual, a new visual paradigm with bio-inspired dynamic perception and μs level temporal resolution, has prominent advantages in many spec...

Assisted documentation as a new focus for artificial intelligence in endoscopy: the precedent of reliable withdrawal time and image reporting.

BACKGROUND : Reliable documentation is essential for maintaining quality standards in endoscopy; however, in clinical practice, report quality varies....

An FDA Guide on Indications for Use and Device Reporting of Artificial Intelligence-Enabled Devices: Significance for Pediatric Use.

Radiology has been a pioneer in adopting artificial intelligence (AI)-enabled devices into the clinic. However, initial clinical experience has identi...

Noninvasive genetic screening: current advances in artificial intelligence for embryo ploidy prediction.

This review discusses the use of artificial intelligence (AI) algorithms in noninvasive prediction of embryo ploidy status for preimplantation genetic...