Obstetrics & Gynecology

Integrating ultrasound-CT-MR for preoperative multi-task prediction in ovarian cancer: achieving diagnostic parity with multidisciplinary team consensus.

Ovarian cancer, with high mortality, demands accurate preoperative assessment to guide individualized treatment. It typically requires ultrasound, CT, and MRI interpreted by multidisciplinary teams (MDTs) in complex cases. We developed OVUCM, a multi-task AI system that integrates multi-modalities via intermediate fusion using radiomics, machine learning, and 5×4 nested cross-validation. Trained o...

Integration of two-dimensional microvascular flow imaging and ultrasound scoring for prediction of placenta accreta spectrum: A prospective study.

OBJECTIVE: This study evaluates the diagnostic performance of two-dimensional (2D) microvascular flow imaging combined with standardized ultrasound markers for predicting placenta accreta spectrum disorders in pregnancies complicated by placenta previa or low-lying placenta. METHODS: This prospective observational study included 61 women with placenta previa or low-lying placenta who underwent ces...

Cell-specific multi-target mechanisms of cotinine in cervical cancer oncogenesis and progression.

BACKGROUND: Cervical cancer is the fourth most common malignant tumor in women globally, with tobacco smoke being a major environmental risk factor. T...

A Hybrid Modelling Framework for the description of friction forces in autoinjector devices.

Autoinjectors (AJs) are medical devices enabling precise subcutaneous self-administration of medicines. An important challenge in modelling these devi...

Validation of Artificial Intelligence in Detecting Acute Cervical Spine Fractures on CT.

BACKGROUND: Cervical spine fractures require prompt and accurate diagnosis to minimize risk of long-term neurological impairment. Artificial intellige...

Construction and validation of a preimplantation kinship identification model using ultra-low-depth whole genome sequencing.

Errors during in vitro fertilization (IVF) workflows pose significant risks; yet, existing quality control measures remain insufficient. Herein, we de...

Economic Impact of a Deep Learning Algorithm for Automated Head and Neck Surgery Referral Triage.

OBJECTIVE: To quantify the comprehensive financial impact from implementing a deep learning algorithm for assistive patient triage within a high-volum...

Deep learning-based prediction of gene expression from histopathology identifies NR5A1 as a candidate biomarker and druggable target in high-grade serous ovarian carcinoma.

BACKGROUND: High-grade serous ovarian cancer (HGSOC) is the most lethal ovarian cancer subtype, responsible for ~ 70% of ovarian cancer-related deaths...

Applying machine-learning models to successful vaginal birth after two cesareans.

BACKGROUND: Vaginal birth after two cesarean deliveries (VBAC2) is increasingly recognized as a reasonable and, in selected cases, preferable option. ...

Spinal cord FDG PET uptake in healthy adults: an AI-driven segmentation study.

PURPOSE: 18F-fluorodeoxyglucose (FDG) Positron Emission Tomography (PET)/Computerized Tomography (CT) is an important imaging modality in oncology, bu...

Analysis of blastocyst morphokinetics assessed by time-lapse technology and its correlation with human IVF treatment outcome.

Human embryo selection in in vitro fertilisation (IVF) treatments is traditionally based on evaluating cell number, morphology, and fragmentation to s...

Deep neural architecture empowered by explainable artificial intelligence for accurate and early diagnosis of gynaecological cancer using medical images.

Early analysis is a necessity for the more effective treatment of cancers. In gynaecological cancers, like endometrial, ovarian, and cervical cancers,...

Interpretable machine learning for endometriosis classification: a rule-based approach.

BACKGROUND: Endometriosis is a chronic gynecological disease characterized by the growth of endometrial-like tissue outside the uterus, leading to pel...

Diagnostic accuracy of an artificial intelligence-based breast ultrasound tool in pregnant and lactating patients.

OBJECTIVES: To assess the diagnostic performance of an artificial intelligence (AI)-based decision support tool for breast ultrasound in pregnant and ...

Biomarker-driven diagnostics and personalized treatment in polycystic ovary syndrome.

Polycystic Ovary Syndrome (PCOS) is a common and clinically heterogeneous endocrine disorder affecting approximately 4-20% of women worldwide. Its com...

Multi-scale feature integration with enhanced cytomorph for high-accuracy cervical cytology classification.

Accurate classification of cervical cytology images plays a crucial role in early detection and prevention of cervical cancer, which remains a signifi...

Gauging support for autonomous delivery drones powered by artificial intelligence: A public survey in Singapore.

There has been emerging empirical evidence supporting the role of artificial intelligence (AI) knowledge in public support for AI. These findings stan...

Redesigning trauma-focused interventions to address capacity challenges in mental health systems.

Despite strong evidence supporting the use of trauma-focused evidence-based psychotherapies (EBPs) to treat posttraumatic stress disorder (PTSD), heal...

Automatic detection of panoramic positioning errors and development of an objective image quality scoring system using deep learning.

OBJECTIVES: To develop a deep learning model capable of automatically detecting common positioning errors in panoramic radiographs and to establish an...

Otolithic Dysfunction in Normal-Hearing Individuals With Tinnitus.

OBJECTIVES: In individuals with normal hearing, tinnitus may be the initial manifestation of cochleovestibular lesions. Tinnitus is a multifactorial s...