Latest AI and machine learning research in obstetrics & gynecology for healthcare professionals.
The unrestrained proliferation of cells that are malignant in nature is cancer. In recent times, medical professionals are constantly acquiring enhanced diagnostic and treatment abilities by implementing deep learning models to analyze medical data for better clinical decision, disease diagnosis and drug discovery. A majority of cancers are studied and treated by incorporating these technologies. ...
Unmanned aerial vehicles (UAVs) are increasingly used to support time-critical medical supply delivery, providing rapid and flexible logistics during emergencies and resource shortages. However, effective deployment of UAV fleets requires coordination mechanisms capable of prioritizing medical requests, allocating limited aerial resources, and adapting delivery schedules under uncertain operationa...
Protein phosphorylation is a key regulator of signaling, with mass spectrometry (MS) based phosphoproteomics serving as the premier technology for its...
Video-based Clinical Gait Analysis often suffers from poor generalization as models overfit environmental biases instead of capturing pathological mot...
DNA extracted from tissue samples typically derive from of a complex mixture of cell types. Without single cell analysis, it has been generally imposs...
A major challenge in biology is predicting how cells transition between states over time and how perturbations disrupt these transitions. Understandin...
Dental crown restoration is one of the most common treatment modalities for tooth defect, where personalized dental crown design is critical. While co...
Identification of early interventions to reduce/eliminate asthma - the most common chronic disease among children - could significantly reduce burden ...
Background: Placental growth and function are imperative for healthy fetal growth; data on placentas can inform research and clinical care. Measuring ...
Breast cancer is the most frequently diagnosed malignancy among women worldwide and a leading cause of cancer-related mortality. Dynamic contrast-enha...
Spatial transcriptomics has transformed our ability to study tissue architecture at molecular resolution, yet analyzing these data demands navigating ...
Endometriosis is a chronic inflammatory condition with significant diagnostic delays impacting one in ten reproductive age women worldwide. While mach...
Clinical risk prediction models often underperform in real-world settings due to poor calibration, limited transportability, and subgroup disparities....
Applying deep learning models to RNA-Seq data poses substantial challenges, primarily due to the high dimensionality of the data and the limited sampl...
Perinatal depression (PD) is common and disabling, yet its longitudinal comorbidity patterns and predictability remain poorly understood. This study l...
The study of histopathological subtypes is valuable for the personalisation of effective treatment strategies for ovarian cancer. However, increasing ...
Background: Risk screening for pre-eclampsia relies on accurate gestational age assessment, but routine access to ultrasound-based gestational dating ...
Aging of hematopoietic stem and progenitor cells (HSPCs) impairs regenerative capacity and predisposes to hematological diseases. Here, we constructed...
Precision medicine requires models that can translate rich molecular measurements into individualized predictions of biological response. Phosphoinosi...
While cervical arthroplasty using Total Disc Replacement (TDR) implants is an established treatment for persistent neck and arm pain, revision rates l...