ADHD/ADD

Combining multimodal fatigue fracture surface images for analysis with a CNN.

This work uses three different modalities, namely SEM, BSE and scanning white light interference (SWLI) to image fatigue fracture surfaces of Ti-6Al-4V. Convolutional neural networks (CNNs) that were pre-trained on images of the natural world were used to predict values such as distance from load line and crack growth rate. SEM images are routinely used to study the topography of fracture surfaces...

Encoding and Decoding of Brain Dynamic Functional Connectivity for ADHD Diagnosis.

Recent studies have demonstrated strong associations between the changes in dynamic functional connectivity (FC) and both behavioral and cognitive functions. The sliding window technique is the most widely used method for evaluating dynamic FC; however, it faces two key challenges: distributional shifts across windows and high dimensionality, as FC is computed across windows of the entire time ser...

System-Specific Reparameterization of Density Functionals with Machine Learning: Application to Spin-Splitting Energies of Transition Metal Complexes.

Accurate estimates of the spin-splitting energy (SSE) are essential for proper modeling of transition metal complex (TMC) catalysts and functional mat...

Early detection of adults ADHD using electronic health records: A machine learning study.

Digital pathology-based artificial intelligence algorithms in prostate cancer: inside the 'black box'.

Artificial intelligence (AI) algorithms leveraging digital pathology slides are currently transforming the way urological cancers are diagnosed and gr...

MRI-based Radiomics and volumetrics for predicting the onset of Alzheimer's Disease with explainable machine learning.

The detection of Alzheimer's Disease (AD) using structural Magnetic Resonance Imaging (MRI) and Machine Learning (ML) often focuses on late-stage atro...

Chronic oil pollution in small ports: A review of the role and potential of AUVs.

Chronic oil pollution in small ports are typically low-level, repeated, and long-lasting, making them difficult to monitor with conventional approache...

Deep learning-based object detection of dental implant systems in panoramic and periapical radiographs.

STATEMENT OF PROBLEM: The manual identification of dental implant systems on radiographs is time-consuming, operator-dependent, and prone to diagnosti...

Plasma ATN biomarkers across the alzheimer's disease continuum in a Chilean community- and clinic-based cohort.

BACKGROUND: Plasma biomarkers have emerged as robust indicators of Alzheimer's disease (AD) pathology, offering accessible tools for staging and strat...

Electrochemical biosensors for Calreticulin in lung Cancer.

Electrochemical biosensors represent an advanced and novel technology for the sensitive and specific detection of clinically relevant biomarkers. Of t...

A Multimodal Dataset for Neurophysiological and AI Applications.

Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder characterized by inattention, hyperactivity, and impulsivit...

Smartphone-Based Portable Slit Lamp in Anterior Segment Diseases: A Narrative Review of Clinical Assessment and Integration with Artificial Intelligence.

Smartphone-based portable slit lamps are rapidly evolving from simple add-ons into practical, low-cost front-line tools for anterior segment care beyo...

Automatic classification method of e-commerce commodity raw materials through the introduction of self-supervised concepts and the construction of domain ontology.

The e-commerce platform's function-oriented classification basis will cause items with the same (different) raw materials to be incorrectly classified...

Cardiovascular Risk Assessment Tools in Chronic Kidney Disease.

Cardiovascular (CV) risk calculators estimate the likelihood of CV events by integrating factors such as age, sex, blood pressure, lipids, smoking, an...

Dual-kingdom necrobiome succession extends postmortem interval estimation into skeletonization.

Forensic estimation of the postmortem interval (PMI) becomes increasingly challenging when decomposition progresses beyond the initial weeks, as tradi...

Predicting the usage of seasonal drugs by utilizing advanced machine learning: An albuterol case study.

Manual forecasting of seasonal medication demand results in inefficiencies and labor burden. With the advancement of machine learning, there is an opp...

Tailored psychotherapy and AI-enhanced contingency management for co-occurring disorders in cannabis use disorder: a systematic review.

BACKGROUND: Cannabis use disorder (CUD) commonly co-occurs with depression, post-traumatic stress disorder (PTSD), anxiety, and attention-deficit/hype...

Incremental prognostic value of immune cell densities beyond clinical parameters in non-small cell lung cancer.

BACKGROUND: Multiplex immunofluorescence imaging enables detailed characterization of the tumor immune microenvironment, but whether immune cell densi...

Fracture risk scores using output from an opportunistic screen of low bone density from conventional X-ray.

Fracture risk is commonly assessed by FRAX, a tool that estimates 10-yr risk for major osteoporotic fracture (MOF) and hip fracture. FRAX scores are o...

Refined trajectory smoothing and deep learning classification of human sperm motility.

STUDY QUESTION: Can precise trajectory smoothing improve extraction of sperm motility features, and can deep learning on raw trajectory data enable ac...