AIMC Topic: Humans

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A hierarchical deep reinforcement learning framework for intelligent automatic treatment planning of prostate cancer intensity modulated radiation therapy.

Physics in medicine and biology
We have previously proposed an intelligent automatic treatment planning (IATP) framework that builds a virtual treatment planner network (VTPN) to operate a treatment planning system (TPS) to generate high-quality radiation therapy (RT) treatment pla...

Contrasting factors associated with COVID-19-related ICU admission and death outcomes in hospitalised patients by means of Shapley values.

PLoS computational biology
Identification of those at greatest risk of death due to the substantial threat of COVID-19 can benefit from novel approaches to epidemiology that leverage large datasets and complex machine-learning models, provide data-driven intelligence, and guid...

Behavioral correlates of cortical semantic representations modeled by word vectors.

PLoS computational biology
The quantitative modeling of semantic representations in the brain plays a key role in understanding the neural basis of semantic processing. Previous studies have demonstrated that word vectors, which were originally developed for use in the field o...

Adaptive Fuzzy Sliding Mode Control of a Pressure-Controlled Artificial Ventilator.

Journal of healthcare engineering
This paper presents the application of adaptive fuzzy sliding mode control (AFSMC) for the respiratory system to assist the patients facing difficulty in breathing. The ventilator system consists of a blower-hose-patient system and patient's lung mod...

Impact of chart image characteristics on stock price prediction with a convolutional neural network.

PloS one
Stock price prediction has long been the subject of research because of the importance of accuracy of prediction and the difficulty in forecasting. Traditionally, forecasting has involved linear models such as AR and MR or nonlinear models such as AN...

Comparison of Radiomic Models Based on Different Machine Learning Methods for Predicting Intracerebral Hemorrhage Expansion.

Clinical neuroradiology
PURPOSE: The objective of this study was to predict hematoma expansion (HE) by radiomic models based on different machine learning methods and determine the best radiomic model through the comparison.

AI-based monitoring of retinal fluid in disease activity and under therapy.

Progress in retinal and eye research
Retinal fluid as the major biomarker in exudative macular disease is accurately visualized by high-resolution three-dimensional optical coherence tomography (OCT), which is used world-wide as a diagnostic gold standard largely replacing clinical exam...

Contrastive rendering with semi-supervised learning for ovary and follicle segmentation from 3D ultrasound.

Medical image analysis
Segmentation of ovary and follicles from 3D ultrasound (US) is the crucial technique of measurement tools for female infertility diagnosis. Since manual segmentation is time-consuming and operator-dependent, an accurate and fast segmentation method i...

A risk grouping algorithm for predicting factors of persistently elevated prostate-specific antigen in patients following robot-assisted radical prostatectomy.

International journal of clinical practice
OBJECTIVE: After radical prostatectomy, prostate-specific antigen(PSA) value measuring ≥0.1 ng/mL is defined as persistent PSA(pPSA) and in many studies, it was found to be associated with aggressive disease and poor prognosis. Our aim in this study ...