Pregnancy

A domain adaptation model for carotid ultrasound: Image harmonization, noise reduction, and impact on cardiovascular risk markers.

Deep learning has been used extensively for medical image analysis applications, assuming the traini...

Development and validation of a framework for registration of whole-mount radical prostatectomy histopathology with three-dimensional transrectal ultrasound.

PURPOSE: Artificial intelligence (AI) has the potential to improve diagnostic imaging on multiple le...

Advanced stability prediction and mechanism study of goji berry beverage via ultrasound-assisted homogenization utilizing genetic algorithm-based backpropagation neural networks.

Traditional cloudy goji berry beverages (CGBs) preparation methods often cause irreversible phase se...

Ultrasound-based radiomics and machine learning for enhanced diagnosis of knee osteoarthritis: Evaluation of diagnostic accuracy, sensitivity, specificity, and predictive value.

PURPOSE: To evaluate the usefulness of radiomics features extracted from ultrasonographic images in ...

Evaluating how different balancing data techniques impact on prediction of premature birth using machine learning models.

Premature birth can be defined as birth before 37 weeks of gestation, which is a significant global ...

Effectiveness and clinical impact of using deep learning for first-trimester fetal ultrasound image quality auditing.

BACKGROUND: Regular auditing of ultrasound images is required to maintain quality; however, manual a...

Automatic Human Embryo Volume Measurement in First Trimester Ultrasound From the Rotterdam Periconception Cohort: Quantitative and Qualitative Evaluation of Artificial Intelligence.

BACKGROUND: Noninvasive volumetric measurements during the first trimester of pregnancy provide uniq...

Prediction of BRAF and TERT status in PTCs by machine learning-based ultrasound radiomics methods: A multicenter study.

BACKGROUND: Preoperative identification of genetic mutations is conducive to individualized treatmen...

Improving realism in abdominal ultrasound simulation combining a segmentation-guided loss and polar coordinates training.

BACKGROUND: Ultrasound (US) simulation helps train physicians and medical students in image acquisit...

Ultrasound-based deep learning to differentiate salivary gland tumors.

OBJECTIVE: Accurate preoperative diagnosis is essential for selecting appropriate surgical intervent...

Intrapartum electronic fetal monitoring and artificial intelligence: a happy marriage?

Deep Learning Based on Ultrasound Images Differentiates Parotid Gland Pleomorphic Adenomas and Warthin Tumors.

Exploring the clinical significance of employing deep learning methodologies on ultrasound images fo...

Guided ultrasound acquisition for nonrigid image registration using reinforcement learning.

We propose a guided registration method for spatially aligning a fixed preoperative image and untrac...

Accurate prediction of mediolateral episiotomy risk during labor: development and verification of an artificial intelligence model.

OBJECTIVE: The study developed an intelligent online evaluation system for mediolateral episiotomy, ...

Placing Objects on Table Is Preferred over Direct Handovers When Users Are Occupied.

Service robots commonly deliver objects through direct handovers, assuming users are fully attentive...

Machine learning combined with infrared spectroscopy for detection of hypertension pregnancy: towards newborn and pregnant blood analysis.

Biochemical changes in the cervix during labor are not well understood. This gap in knowledge is sig...

Cesarean Scar Pregnancy Prognostic Classification System Based on Machine-Learning and Traditional Linear Scoring Models.

OBJECTIVES: Cesarean scar pregnancy (CSP) refers to a special type of pregnancy with a variable prog...

Interpretable machine learning-based insights into early-life endocrine disruptor exposure and small vulnerable newborns.

Early-life exposure to endocrine-disrupting chemicals (EDCs) may contribute to small vulnerable newb...

Predicting Risk for Patent Ductus Arteriosus in the Neonate: A Machine Learning Analysis.

: Patent ductus arteriosus (PDA) is common in newborns, being associated with high morbidity and mor...

Harnessing the oloid shape in magnetically driven robots to enable high-resolution ultrasound imaging.

Magnetic fields enable remote manipulation of objects and are ideal for medical applications because...

Thyroid nodule classification in ultrasound imaging using deep transfer learning.

BACKGROUND: The accurate diagnosis of thyroid nodules represents a critical and frequently encounter...