Pregnancy

HVAngleEst: A Dataset for End-to-end Automated Hallux Valgus Angle Measurement from X-Ray Images.

Accurate measurement of hallux valgus angle (HVA) and intermetatarsal angle (IMA) is essential for diagnosing hallux valgus and determining appropriate treatment strategies. Traditional manual measurement methods, while standardized, are time-consuming, labor-intensive, and subject to evaluator bias. Recent advancements in deep learning have been applied to hallux valgus angle estimation, but the ...

Artificial Intelligence's Role in Improving Adverse Pregnancy Outcomes: A Scoping Review and Consideration of Ethical Issues.

: Adverse pregnancy outcomes (APOs), which include hypertensive disorders of pregnancy (gestational hypertension, preeclampsia, and related disorders), gestational diabetes, preterm birth, fetal growth restriction, low birth weight, small-for-gestational-age newborn, placental abruption, and stillbirth, are health risks for pregnant women that can have fatal outcomes. This study's aim is to invest...

Machine learning and explainable artificial intelligence to predict and interpret lead toxicity in pregnant women and unborn baby.

INTRODUCTION: Lead toxicity is a well-recognised environmental health issue, with prenatal exposure posing significant risks to infants. One major pat...

A Novel and Modern Calculator to Predict Vaginal Birth after Cesarean Delivery.

Counseling patients who are considering a trial of labor after cesarean (TOLAC) is a challenging task given the risks and benefits of either approach....

Predicting abnormal fetal growth using deep learning.

Ultrasound assessment of fetal size and growth is the mainstay of monitoring fetal well-being during pregnancy, as being small for gestational age (SG...

Bi-modal ultrasound radiomics and habitat analysis enhanced the pre-operative prediction of axillary lymph node burden in patients with early-stage breast cancer.

OBJECTIVE: This study aimed to evaluate the value of habitat analysis based bi-modal ultrasound radiomics in predicting axillary lymph node (ALN) stat...

Magnetoliposomes for nanomedicine: synthesis, characterization, and applications in drug, gene, and peptide delivery.

INTRODUCTION: Magnetoliposomes represent a transformative advancement in nanomedicine by integrating magnetic nanoparticles with liposomal structures,...

Contrast-Enhanced Ultrasound for Hepatocellular Carcinoma Diagnosis- Expert Panel Narrative Review.

Despite growing clinical use of contrast-enhanced ultrasound (CEUS), inconsistency remains in the modality's role in clinical pathways for hepatocellu...

An automatic approach for the classification of lumpy skin disease in cattle.

Lumpy Skin Disease (LSD) presents significant risks and economic challenges to global cattle farming. Effective and accurate classification of LSD is ...

Efficient feature extraction using light-weight CNN attention-based deep learning architectures for ultrasound fetal plane classification.

Ultrasound fetal imaging is beneficial to support prenatal development because it is affordable and non-intrusive. Nevertheless, fetal plane classific...

Incorporating organ deformation in biological modeling and patient outcome study for permanent prostate brachytherapy.

Permanent prostate brachytherapy has inherent intraoperative organ deformation due to the inflatable trans-rectal ultrasound probe cover. Since the ma...

An orchestration learning framework for ultrasound imaging: Prompt-Guided Hyper-Perception and Attention-Matching Downstream Synchronization.

Ultrasound imaging is pivotal in clinical diagnostics due to its affordability, portability, safety, real-time capability, and non-invasive nature. It...

PlaNet-S: an Automatic Semantic Segmentation Model for Placenta Using U-Net and SegNeXt.

This study aimed to develop a fully automated semantic placenta segmentation model that integrates the U-Net and SegNeXt architectures through ensembl...

Improving Breast Cancer Diagnosis in Ultrasound Images Using Deep Learning with Feature Fusion and Attention Mechanism.

RATIONALE AND OBJECTIVES: Early detection of malignant lesions in ultrasound images is crucial for effective cancer diagnosis and treatment. While tra...

Perinatal responsibility in a fragmented world: reflections from the 2024 international academy of perinatal medicine New York meeting.

This editorial introduces the Special Issue of the Journal of Perinatal Medicine dedicated to the 2024 New York meeting of the International Academy o...

Use video comprehension technology to diagnose ultrasound pneumothorax like a doctor would.

INTRODUCTION: Emergency rescue scenes and pre-hospital emergency stages commonly encounter trauma victims. Life-saving measures must be taken at the s...

AI-based multimodal prediction of lymph node metastasis and capsular invasion in cT1N0M0 papillary thyroid carcinoma.

BACKGROUND: Accurate preoperative evaluation of cT1N0M0 papillary thyroid carcinoma (PTC) is essential for guiding appropriate treatment strategies. A...

Can intraoperative improvement of radial endobronchial ultrasound imaging enhance the diagnostic yield in peripheral pulmonary lesions?

BACKGROUND: Data regarding the diagnostic efficacy of radial endobronchial ultrasound (R-EBUS) findings obtained via transbronchial needle aspiration ...

Promises and perils of generative artificial intelligence: a narrative review informing its ethical and practical applications in clinical exercise physiology.

Generative Artificial Intelligence (GenAI) is transforming various sectors, including healthcare, offering both promising opportunities and notable ri...

Advances in brain-targeted delivery strategies and natural product-mediated enhancement of blood-brain barrier permeability.

The blood-brain barrier (BBB) represents a formidable challenge in the treatment of neurological disorders, as it restricts the passage of most therap...