AIMC Topic: Male

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A Machine-Learning Model for Lung Age Forecasting by Analyzing Exhalations.

Sensors (Basel, Switzerland)
Spirometers are important devices for following up patients with respiratory diseases. These are mainly located only at hospitals, with all the disadvantages that this can entail. This limits their use and consequently, the supervision of patients. R...

Application of deep learning image reconstruction in low-dose chest CT scan.

The British journal of radiology
OBJECTIVE: Deep learning image reconstruction (DLIR) is a new reconstruction method for maintaining image quality at reduced radiation dose. The purpose of this study was to compare image quality of reduced-dose DLIR images with the standard-dose ada...

Deep learning-based artificial intelligence for prostate cancer detection at biparametric MRI.

Abdominal radiology (New York)
PURPOSE: To present fully automated DL-based prostate cancer detection system for prostate MRI.

Effect of head motion-induced artefacts on the reliability of deep learning-based whole-brain segmentation.

Scientific reports
Due to their robustness and speed, recently developed deep learning-based methods have the potential to provide a faster and hence more scalable alternative to more conventional neuroimaging analysis pipelines in terms of whole-brain segmentation bas...

Dosimetric impact of deep learning-based CT auto-segmentation on radiation therapy treatment planning for prostate cancer.

Radiation oncology (London, England)
BACKGROUND: The evaluation of automatic segmentation algorithms is commonly performed using geometric metrics. An analysis based on dosimetric parameters might be more relevant in clinical practice but is often lacking in the literature. The aim of t...

Nurturing diversity and inclusion in AI in Biomedicine through a virtual summer program for high school students.

PLoS computational biology
Artificial Intelligence (AI) has the power to improve our lives through a wide variety of applications, many of which fall into the healthcare space; however, a lack of diversity is contributing to limitations in how broadly AI can help people. The U...

Agreement of anthropometric and body composition measures predicted from 2D smartphone images and body impedance scales with criterion methods.

Obesity research & clinical practice
BACKGROUND/OBJECTIVES: Body composition and anthropometry assessment from two-dimensional smartphone images is possible through advancement of computational hardware and artificial intelligence (AI) techniques. This study established agreement of a n...

Impact of the severity of urethrovesical anastomotic leakage on urinary continence following robot-assisted laparoscopic prostatectomy.

Journal of robotic surgery
We assessed whether the severity of anastomotic urinary leakage detected during routine cystourethrography after robot-assisted laparoscopic prostatectomy (RALP) affects urinary continence recovery. Around 302 patients who underwent RALP between Augu...

Assessing pentafecta achievement after robot-assisted radical cystectomy and its association with surgical experience: Results from a high-volume institution.

Urologic oncology
OBJECTIVES: Radical cystectomy (RC) represents the gold standard treatment for high-risk bladder cancer. Despite evidence suggesting that surgical experience correlates with perioperative and oncologic outcomes of robot-assisted RC (RARC), validated ...

Propofol Anesthesia Depth Monitoring Based on Self-Attention and Residual Structure Convolutional Neural Network.

Computational and mathematical methods in medicine
METHODS: We compare nine index values, select CNN+EEG, which has good correlation with BIS index, as an anesthesia state observation index to identify the parameters of the model, and establish a model based on self-attention and dual resistructure c...