AIMC Topic: Humans

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Flow starvation during square-flow assisted ventilation detected by supervised deep learning techniques.

Critical care (London, England)
BACKGROUND: Flow starvation is a type of patient-ventilator asynchrony that occurs when gas delivery does not fully meet the patients' ventilatory demand due to an insufficient airflow and/or a high inspiratory effort, and it is usually identified by...

Deep learning algorithms for predicting renal replacement therapy initiation in CKD patients: a retrospective cohort study.

BMC nephrology
BACKGROUND: Chronic kidney disease (CKD) requires accurate prediction of renal replacement therapy (RRT) initiation risk. This study developed deep learning algorithms (DLAs) to predict RRT risk in CKD patients by incorporating medical history and pr...

NuInsSeg: A fully annotated dataset for nuclei instance segmentation in H&E-stained histological images.

Scientific data
In computational pathology, automatic nuclei instance segmentation plays an essential role in whole slide image analysis. While many computerized approaches have been proposed for this task, supervised deep learning (DL) methods have shown superior s...

Identification of kidney stones in KUB X-ray images using VGG16 empowered with explainable artificial intelligence.

Scientific reports
A kidney stone is a solid formation that can lead to kidney failure, severe pain, and reduced quality of life from urinary system blockages. While medical experts can interpret kidney-ureter-bladder (KUB) X-ray images, specific images pose challenges...

Analysis and evaluation of explainable artificial intelligence on suicide risk assessment.

Scientific reports
This study explores the effectiveness of Explainable Artificial Intelligence (XAI) for predicting suicide risk from medical tabular data. Given the common challenge of limited datasets in health-related Machine Learning (ML) applications, we use data...

Deep learning model to predict lupus nephritis renal flare based on dynamic multivariable time-series data.

BMJ open
OBJECTIVES: To develop an interpretable deep learning model of lupus nephritis (LN) relapse prediction based on dynamic multivariable time-series data.

Implications of conscious AI in primary healthcare.

Family medicine and community health
The conversation about consciousness of artificial intelligence (AI) is an ongoing topic since 1950s. Despite the numerous applications of AI identified in healthcare and primary healthcare, little is known about how a conscious AI would reshape its ...

Prognostic factors among patients with pathological Grade Group 5 prostate cancer based on robot-associated radical prostatectomy specimens from a large Japanese cohort (MSUG94).

World journal of urology
PURPOSE: There are no definitive prognostic factors for patients with pathological Grade Group 5 (pGG 5) prostate cancer (PCa) undergoing robot-associated radical prostatectomy (RARP). This study aimed to explore the prognostic factors among patients...

Enhancing pediatric pneumonia diagnosis through masked autoencoders.

Scientific reports
Pneumonia, an inflammatory lung condition primarily triggered by bacteria, viruses, or fungi, presents distinctive challenges in pediatric cases due to the unique characteristics of the respiratory system and the potential for rapid deterioration. Ti...

Image quality and metal artifact reduction in total hip arthroplasty CT: deep learning-based algorithm versus virtual monoenergetic imaging and orthopedic metal artifact reduction.

European radiology experimental
BACKGROUND: To compare image quality, metal artifacts, and diagnostic confidence of conventional computed tomography (CT) images of unilateral total hip arthroplasty patients (THA) with deep learning-based metal artifact reduction (DL-MAR) to convent...