AIMC Topic: Female

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Comparative Effectiveness Analysis of Lumpectomy and Mastectomy for Elderly Female Breast Cancer Patients: A Deep Learning-based Big Data Analysis.

The Yale journal of biology and medicine
: To evaluate the comparative effectiveness of treatments, a randomized clinical trial remains the gold standard but can be challenged by a high cost, a limited sample size, an inability to fully reflect the real world, and feasibility concerns. The ...

An intelligent adverse delivery outcomes prediction model based on the fusion of multiple obstetric clinical data.

Computer methods in biomechanics and biomedical engineering
Adverse delivery outcomes is a major re-productive health problem that affects the physical and mental health of pregnant women. Obviously, obstetric clinical data has periodically time series characteristics. This paper proposed a three stage advers...

Developing tongue coating status assessment using image recognition with deep learning.

Journal of prosthodontic research
PURPOSE: To build an image recognition network to evaluate tongue coating status.

Impact of heart failure on reoperation in adult congenital heart disease: An innovative machine learning model.

The Journal of thoracic and cardiovascular surgery
OBJECTIVES: The study objectives were to evaluate the association between preoperative heart failure and reoperative cardiac surgical outcomes in adult congenital heart disease and to develop a risk model for postoperative morbidity/mortality.

Exploring the Potential of ChatGPT-4 in Responding to Common Questions About Abdominoplasty: An AI-Based Case Study of a Plastic Surgery Consultation.

Aesthetic plastic surgery
BACKGROUND: With the increasing integration of artificial intelligence (AI) in health care, AI chatbots like ChatGPT-4 are being used to deliver health information.

Machine Learning for the Prediction of Survival Post-Allogeneic Hematopoietic Cell Transplantation: A Single-Center Experience.

Acta haematologica
INTRODUCTION: Prediction of outcomes following allogeneic hematopoietic cell transplantation (HCT) remains a major challenge. Machine learning (ML) is a computational procedure that may facilitate the generation of HCT prediction models. We sought to...

A deep learning image analysis method for renal perfusion estimation in pseudo-continuous arterial spin labelling MRI.

Magnetic resonance imaging
Accurate segmentation of renal tissues is an essential step for renal perfusion estimation and postoperative assessment of the allograft. Images are usually manually labeled, which is tedious and prone to human error. We present an image analysis met...

Accuracy of liver metastasis detection and characterization: Dual-energy CT versus single-energy CT with deep learning reconstruction.

European journal of radiology
PURPOSE: To assess whether image quality differences between SECT (single-energy CT) and DECT (dual-energy CT 70 keV) with equivalent radiation doses result in altered detection and characterization accuracy of liver metastases when using deep learni...

Recent advancements in machine learning and deep learning-based breast cancer detection using mammograms.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
OBJECTIVE: Mammogram-based automatic breast cancer detection has a primary role in accurate cancer diagnosis and treatment planning to save valuable lives. Mammography is one basic yet efficient test for screening breast cancer. Very few comprehensiv...

Robotic and laparoscopic gynaecological surgery: a prospective multicentre observational cohort study and economic evaluation in England.

BMJ open
OBJECTIVE: To compare the health-related quality of life and cost-effectiveness of robot-assisted laparoscopic surgery (RALS) versus conventional 'straight stick' laparoscopic surgery (CLS) in women undergoing hysterectomy as part of their treatment ...