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A Comprehensive AI-Based Approach in Classifying Breast Lesions: Focusing on Improving Pathologists' Accuracy and Efficiency.

Clinical breast cancer
BACKGROUND: Accurate classification of breast lesions is essential for effective clinical decision-making and patient management. In this study, we evaluated an artificial intelligence (AI) solution to classify whole slide images (WSIs) of breast les...

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

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: Cesarean scar pregnancy (CSP) refers to a special type of pregnancy with a variable prognosis. We aimed to establish a prognostic classification system using ultrasound and clinical features to provide a reference for management strategie...

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

Journal of hazardous materials
Early-life exposure to endocrine-disrupting chemicals (EDCs) may contribute to small vulnerable newborns, including conditions such as being small for gestational age (SGA) and preterm birth (PTB), yet evidence remains limited. This study, which is b...

Predicting quality of life of patients after treatment for spinal metastatic disease: development and internal evaluation.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: When treating spinal metastases in a palliative setting, maintaining or enhancing quality of life (QoL) is the primary therapeutic objective. Clinicians tailor their treatment strategy by weighing the QoL benefits against expected...

A Novel Visual Model for Predicting Prognosis of Resected Hepatoblastoma: A Multicenter Study.

Academic radiology
RATIONALE AND OBJECTIVES: This study aimed to evaluate the application of a contrast-enhanced CT-based visual model in predicting postoperative prognosis in patients with hepatoblastoma (HB).

Human bone ultrastructure in 3D: Multimodal correlative study combining nanoscale X-ray computed tomography and quantitative polarized Raman spectroscopy.

Acta biomaterialia
Unique mechanical properties of cortical bone are defined by the arrangement and ratio of its organic and inorganic constituents. This arrangement can be influenced by ageing and disease, urging the understanding of normal and deviant morphological p...

Artificial intelligence-based virtual staining platform for identifying tumor-associated macrophages from hematoxylin and eosin-stained images.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: Virtual staining is an artificial intelligence-based approach that transforms pathology images between stain types, such as hematoxylin and eosin (H&E) to immunohistochemistry (IHC), providing a tissue-preserving and efficient alternative...

Breast cancer detection and classification: A study on the specification and implementation of multilayer perceptron analog artificial neural networks.

Computers in biology and medicine
Breast cancer is a leading cause of mortality worldwide. Screening therefore remains the best defense against this disease, highlighting the need for accurate and efficient diagnostic methods. Previous authors addressed this issue by implementing dig...

Distinguishing severe sleep apnea from habitual snoring using a neck-wearable piezoelectric sensor and deep learning: A pilot study.

Computers in biology and medicine
This study explores the development of a deep learning model using a neck-wearable piezoelectric sensor to accurately distinguish severe sleep apnea syndrome (SAS) from habitual snoring, addressing the underdiagnosis of SAS in adults. From 2018 to 20...