AIMC Topic: Deep Learning

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Development of an anthropomorphic multimodality pelvic phantom for quantitative evaluation of a deep-learning-based synthetic computed tomography generation technique.

Journal of applied clinical medical physics
PURPOSE: The objective of this study was to fabricate an anthropomorphic multimodality pelvic phantom to evaluate a deep-learning-based synthetic computed tomography (CT) algorithm for magnetic resonance (MR)-only radiotherapy.

Learning deep neural networks' architectures using differential evolution. Case study: Medical imaging processing.

Computers in biology and medicine
The COVID-19 pandemic has changed the way we practice medicine. Cancer patient and obstetric care landscapes have been distorted. Delaying cancer diagnosis or maternal-fetal monitoring increased the number of preventable deaths or pregnancy complicat...

Explicit and automatic ejection fraction assessment on 2D cardiac ultrasound with a deep learning-based approach.

Computers in biology and medicine
BACKGROUND: Ejection fraction (EF) is a key parameter for assessing cardiovascular functions in cardiac ultrasound, but its manual assessment is time-consuming and subject to high inter and intra-observer variability. Deep learning-based methods have...

Early diagnosis of Alzheimer's disease based on deep learning: A systematic review.

Computers in biology and medicine
BACKGROUND: The improvement of health indicators and life expectancy, especially in developed countries, has led to population growth and increased age-related diseases, including Alzheimer's disease (AD). Thus, the early detection of AD is valuable ...

Utilization of Random Forest and Deep Learning Neural Network for Predicting Factors Affecting Perceived Usability of a COVID-19 Contact Tracing Mobile Application in Thailand "ThaiChana".

International journal of environmental research and public health
The continuous rise of the COVID-19 Omicron cases despite the vaccination program available has been progressing worldwide. To mitigate the COVID-19 contraction, different contact tracing applications have been utilized such as Thai Chana from Thaila...

Identifying common transcriptome signatures of cancer by interpreting deep learning models.

Genome biology
BACKGROUND: Cancer is a set of diseases characterized by unchecked cell proliferation and invasion of surrounding tissues. The many genes that have been genetically associated with cancer or shown to directly contribute to oncogenesis vary widely bet...

Deep learning model for the automatic classification of COVID-19 pneumonia, non-COVID-19 pneumonia, and the healthy: a multi-center retrospective study.

Scientific reports
This retrospective study aimed to develop and validate a deep learning model for the classification of coronavirus disease-2019 (COVID-19) pneumonia, non-COVID-19 pneumonia, and the healthy using chest X-ray (CXR) images. One private and two public d...

Deep learning modeling mA deposition reveals the importance of downstream cis-element sequences.

Nature communications
The N-methyladenosine (mA) modification is deposited to nascent transcripts on chromatin, but its site-specificity mechanism is mostly unknown. Here we model the mA deposition to pre-mRNA by iM6A (intelligent mA), a deep learning method, demonstratin...

Expert surgeons and deep learning models can predict the outcome of surgical hemorrhage from 1 min of video.

Scientific reports
Major vascular injury resulting in uncontrolled bleeding is a catastrophic and often fatal complication of minimally invasive surgery. At the outset of these events, surgeons do not know how much blood will be lost or whether they will successfully c...