AIMC Topic: Middle Aged

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Artificial intelligence for detecting electrolyte imbalance using electrocardiography.

Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc
INTRODUCTION: The detection and monitoring of electrolyte imbalance is essential for appropriate management of many metabolic diseases; however, there is no tool that detects such imbalances reliably and noninvasively. In this study, we developed a d...

Expanding TNM for lung cancer through machine learning.

Thoracic cancer
BACKGROUND: Expanding the tumor, lymph node, metastasis (TNM) staging system by accommodating new prognostic and predictive factors for cancer will improve patient stratification and survival prediction. Here, we introduce machine learning for incorp...

Application of artificial intelligence-based computer-assisted diagnosis on synthetic mammograms from breast tomosynthesis: comparison with digital mammograms.

European radiology
OBJECTIVE: To compare the diagnostic agreement and performances of synthetic and conventional mammograms when artificial intelligence-based computer-assisted diagnosis (AI-CAD) is applied.

Improving glomerular filtration rate estimation by semi-supervised learning: a development and external validation study.

International urology and nephrology
BACKGROUND: Accurate estimating glomerular filtration rate (GFR) is crucial both in clinical practice and epidemiological survey. We incorporated semi-supervised learning technology to improve GFR estimation performance.

Genetic-fuzzy logic model for a non-invasive measurement of a stroke volume.

Computer methods and programs in biomedicine
BACKGROUND: Despite the importance of stroke volume readings in understanding the work of the cardiovascular system in patients, its routine daily measurement outside of a hospital in the absence of special equipment presents a problem for a comprehe...

Machine learning for the prediction of bone metastasis in patients with newly diagnosed thyroid cancer.

Cancer medicine
OBJECTIVES: This study aimed to establish a machine learning prediction model that can be used to predict bone metastasis (BM) in patients with newly diagnosed thyroid cancer (TC).

Predicting gastric cancer outcome from resected lymph node histopathology images using deep learning.

Nature communications
N-staging is a determining factor for prognostic assessment and decision-making for stage-based cancer therapeutic strategies. Visual inspection of whole-slides of intact lymph nodes is currently the main method used by pathologists to calculate the ...

Machine Learning Generated Synthetic Faces for Use in Facial Aesthetic Research.

Facial plastic surgery & aesthetic medicine
A centralized repository of clinically applicable facial images with unrestricted use would facilitate facial aesthetic research. Using a machine learning neural network, we aim to (1) create a repository of synthetic faces that can be used for fac...