AIMC Topic: Female

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Review on Deep Learning-Based CAD Systems for Breast Cancer Diagnosis.

Technology in cancer research & treatment
Breast Cancer (BC) is a major health issue in women of the age group above 45. Identification of BC at an earlier stage is important to reduce the mortality rate. Image-based noninvasive methods are used for early detection and for providing appropri...

Interpretable Estimation of Suicide Risk and Severity from Complete Blood Count Parameters with Explainable Artificial Intelligence Methods.

Psychiatria Danubina
BACKGROUND: The peripheral inflammatory markers are important in the pathophysiology of suicidal behavior. However, methods for practical uses haven't been developed enough yet. This study developed predictive models based on explainable artificial i...

Extent of use of artificial intelligence & machine learning protocols in cancer diagnosis: A scoping review.

The Indian journal of medical research
BACKGROUND & OBJECTIVES: Artificial intelligence (AI) and machine learning (ML) have shown promising results in cancer diagnosis in validation tests involving retrospective patient databases. This study was aimed to explore the extent of actual use o...

Deep learning for differentiating benign from malignant tumors on breast-specific gamma image.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Breast diseases are a significant health threat for women. With the fast-growing BSGI data, it is becoming increasingly critical for physicians to accurately diagnose benign as well as malignant breast tumors.

Direct Dose Prediction With Deep Learning for Postoperative Cervical Cancer Underwent Volumetric Modulated Arc Therapy.

Technology in cancer research & treatment
PURPOSE: To predict the voxel-based dose distribution for postoperative cervical cancer patients underwent volumetric modulated arc therapy using deep learning models.

Prediction of Axillary Lymph Node Metastatic Load of Breast Cancer Based on Ultrasound Deep Learning Radiomics Nomogram.

Technology in cancer research & treatment
Axillary lymph node (ALN) metastatic load is very important in the diagnosis and treatment of breast cancer (BC). We aimed to construct a model for predicting ALN metastatic load using deep learning radiomics (DLR) techniques based on the preoperati...

Statistical and Machine Learning Methods for Discovering Prognostic Biomarkers for Survival Outcomes.

Methods in molecular biology (Clifton, N.J.)
Discovering molecular biomarkers for predicting patient survival outcomes is an essential step toward improving prognosis and therapeutic decision-making in the treatment of severe diseases such as cancer. Due to the high-dimensionality nature of omi...

Machine learning analysis of breast ultrasound to classify triple negative and HER2+ breast cancer subtypes.

Breast disease
OBJECTIVES: Early diagnosis of triple-negative (TN) and human epidermal growth factor receptor 2 positive (HER2+) breast cancer is important due to its increased risk of micrometastatic spread necessitating early treatment and for guiding targeted th...

The Use of Artificial Intelligence for Complete Cytoreduction Prediction in Epithelial Ovarian Cancer: A Narrative Review.

Cancer control : journal of the Moffitt Cancer Center
INTRODUCTION: In patients affected by epithelial ovarian cancer (EOC) complete cytoreduction (CC) has been associated with higher survival outcomes. Artificial intelligence (AI) systems have proved clinical benefice in different areas of healthcare.

[Robot-assisted choledochal cyst resection in a child].

Khirurgiia
The generally accepted method for choledochal cysts is total resection of cystic extrahepatic bile ducts and gallbladder followed by biliodigestive anastomosis. Minimally invasive interventions have recently become the «gold» standard in pediatric he...