HIV/AIDS

Using machine learning to distinguish between authentic and imitation Jackson Pollock poured paintings: A tile-driven approach to computer vision.

Jackson Pollock's abstract poured paintings are celebrated for their striking aesthetic qualities. They are also among the most financially valued and imitated artworks, making them vulnerable to high-profile controversies involving Pollock-like paintings of unknown origin. Given the increased employment of artificial intelligence applications across society, we investigate whether established mac...

Virtual indigo carmine chromoendoscopy images: a novel modality for peroral cholangioscopy using artificial intelligence technology (with video).

BACKGROUND AND AIMS: Accurately diagnosing biliary strictures is crucial for surgical decisions, and although peroral cholangioscopy (POCS) aids in visual diagnosis, diagnosing malignancies or determining lesion margins via this route remains challenging. Indigo carmine is commonly used to evaluate lesions during GI endoscopy. We aimed to establish the utility of virtual indigo carmine chromoendos...

Artificial Intelligence in Otology and Neurotology.

Clinical applications of artificial intelligence (AI) have grown exponentially with increasing computational power and Big Data. Data rich fields such...

Application of an ensemble CatBoost model over complex dataset for vehicle classification.

The classification of vehicles presents notable challenges within the domain of image processing. Traditional models suffer from inefficiency, prolong...

Deep learning restores speech intelligibility in multi-talker interference for cochlear implant users.

Cochlear implants (CIs) do not offer the same level of effectiveness in noisy environments as in quiet settings. Current single-microphone noise reduc...

Unraveling sex differences in Parkinson's disease through explainable machine learning.

Sex differences affect Parkinson's disease (PD) development and manifestation. Yet, current PD identification and treatments underuse these distinctio...

PTransIPs: Identification of Phosphorylation Sites Enhanced by Protein PLM Embeddings.

Phosphorylation is pivotal in numerous fundamental cellular processes and plays a significant role in the onset and progression of various diseases. T...

LDSG-Net: an efficient lightweight convolutional neural network for acute hypotensive episode prediction during ICU hospitalization.

. Acute hypotension episode (AHE) is one of the most critical complications in intensive care unit (ICU). A timely and precise AHE prediction system c...

Application of Machine Learning Methods to Investigate Joint Load in Agility on the Football Field: Creating the Model, Part I.

Laboratory studies have limitations in screening for anterior cruciate ligament (ACL) injury risk due to their lack of ecological validity. Machine le...

Use of machine learning approaches to predict transition of retention in care among people living with HIV in South Carolina: a real-world data study.

Maintaining retention in care (RIC) for people living with HIV (PLWH) helps achieve viral suppression and reduce onward transmission. This study aims ...

Optimized attention-induced multihead convolutional neural network with efficientnetv2-fostered melanoma classification using dermoscopic images.

Melanoma is an uncommon and dangerous type of skin cancer. Dermoscopic imaging aids skilled dermatologists in detection, yet the nuances between melan...

Machine learning with taxonomic family delimitation aids in the classification of ephemeral beaked whale events in passive acoustic monitoring.

Passive acoustic monitoring is an essential tool for studying beaked whale populations. This approach can monitor elusive and pelagic species, but the...

Dissatisfaction-considered waiting time prediction for outpatients with interpretable machine learning.

Long waiting time in outpatient departments is a crucial factor in patient dissatisfaction. We aim to analytically interpret the waiting times predict...

The utility of artificial intelligence in identifying radiological evidence of lung cancer and pulmonary tuberculosis in a high-burden tuberculosis setting.

BACKGROUND: Artificial intelligence (AI), using deep learning (DL) systems, can be utilised to detect radiological changes of various pulmonary diseas...

A 36-nW Electrocardiogram Anomaly Detector Based on a 1.5-bit Non-Feedback Delta Quantizer for Always-on Cardiac Monitoring.

An always-on electrocardiogram (ECG) anomaly detector (EAD) with ultra-low power (ULP) consumption is proposed for continuous cardiac monitoring appli...

Proximal femur fracture detection on plain radiography via feature pyramid networks.

Hip fractures exceed 250,000 cases annually in the United States, with the worldwide incidence projected to increase by 240-310% by 2050. Hip fracture...

Improving HIV preexposure prophylaxis uptake with artificial intelligence and automation: a systematic review.

OBJECTIVES: To identify studies promoting the use of artificial intelligence (AI) or automation with HIV preexposure prophylaxis (PrEP) care and explo...

Assessment and classification of COVID-19 DNA sequence using pairwise features concatenation from multi-transformer and deep features with machine learning models.

The 2019 novel coronavirus (renamed SARS-CoV-2, and generally referred to as the COVID-19 virus) has spread to 184 countries with over 1.5 million con...

Distillation of multi-class cervical lesion cell detection via synthesis-aided pre-training and patch-level feature alignment.

Automated detection of cervical abnormal cells from Thin-prep cytologic test (TCT) images is crucial for efficient cervical abnormal screening using c...

A Novel Deep Learning Approach for Forecasting Myocardial Infarction Occurrences with Time Series Patient Data.

Myocardial Infarction (MI) commonly referred to as a heart attack, results from the abrupt obstruction of blood supply to a section of the heart muscl...