AIMC Topic: Female

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ICSDA: a multi-modal deep learning model to predict breast cancer recurrence and metastasis risk by integrating pathological, clinical and gene expression data.

Briefings in bioinformatics
Breast cancer patients often have recurrence and metastasis after surgery. Predicting the risk of recurrence and metastasis for a breast cancer patient is essential for the development of precision treatment. In this study, we proposed a novel multi-...

Deep learning radiomics under multimodality explore association between muscle/fat and metastasis and survival in breast cancer patients.

Briefings in bioinformatics
Sarcopenia is correlated with poor clinical outcomes in breast cancer (BC) patients. However, there is no precise quantitative study on the correlation between body composition changes and BC metastasis and survival. The present study proposed a deep...

Prospective Validation of a Machine Learning Model for Low-Density Lipoprotein Cholesterol Estimation.

Laboratory medicine
OBJECTIVE: We aim to prospectively validate a previously developed machine learning algorithm for low-density lipoprotein cholesterol (LDL-C) estimation.

Important feature identification for perceptual sex of point-light walkers using supervised machine learning.

Journal of vision
The present study aimed to elucidate the dynamic features that are highly predictive in the biological and perceptual sex classification of point-light walkers (PLWs) and how these features behave in sex classification using supervised machine learni...

[Clinical analysis of three-dimensional surgical planning system for guiding robot-assisted selective artery clamping partial nephrectomy in completely endophytic renal tumor].

Zhonghua wai ke za zhi [Chinese journal of surgery]
To examine the safety and feasibility of three-dimensional (3D) surgical planning system for guiding robot-assisted selective artery clamping partial nephrectomy (RASPN) in completely endophytic renal tumor. Clinical data of 32 patients who suffere...

Strike Velocity Prediction of Stick Blunt Instruments Based on Backpropagation Neural Network.

Fa yi xue za zhi
OBJECTIVES: To analyze and predict the striking velocity range of stick blunt instruments in different populations, and to provide basic data for the biomechanical analysis of blunt force injuries in forensic identification.

BRACS: A Dataset for BReAst Carcinoma Subtyping in H&E Histology Images.

Database : the journal of biological databases and curation
Breast cancer is the most commonly diagnosed cancer and registers the highest number of deaths for women. Advances in diagnostic activities combined with large-scale screening policies have significantly lowered the mortality rates for breast cancer ...

Present and future of machine learning in breast surgery: systematic review.

The British journal of surgery
BACKGROUND: Machine learning is a set of models and methods that can automatically detect patterns in vast amounts of data, extract information, and use it to perform decision-making under uncertain conditions. The potential of machine learning is si...

Past, Present, and Future of Machine Learning and Artificial Intelligence for Breast Cancer Screening.

Journal of breast imaging
Breast cancer screening has evolved substantially over the past few decades because of advancements in new image acquisition systems and novel artificial intelligence (AI) algorithms. This review provides a brief overview of the history, current stat...

Robot-assisted rehabilitation for total knee or hip replacement surgery patients: A systematic review and meta-analysis.

Medicine
BACKGROUND: This study was performed to update the current evidence and evaluate the effects of robot-assisted rehabilitation (RAR) in comparison with conventional rehabilitation (CR) in patients following total knee (TKR) or hip replacements (THR).