AIMC Topic: Deep Learning

Clear Filters Showing 24261 to 24270 of 28423 articles

Deep learning-based CAD system for Alzheimer's diagnosis using deep downsized KPLS.

Scientific reports
Alzheimer's disease (AD) is the most prevalent type of dementia. It is linked with a gradual decline in various brain functions, such as memory. Many research efforts are now directed toward non-invasive procedures for early diagnosis because early d...

Near-zero photon bioimaging by fusing deep learning and ultralow-light microscopy.

Proceedings of the National Academy of Sciences of the United States of America
Enhancing the reliability and reproducibility of optical microscopy by reducing specimen irradiance continues to be an important biotechnology target. As irradiance levels are reduced, however, the particle nature of light is heightened, giving rise ...

Closing the gap in the clinical adoption of computational pathology: a standardized, open-source framework to integrate deep-learning models into the laboratory information system.

Genome medicine
BACKGROUND: Digital pathology (DP) has revolutionized cancer diagnostics and enabled the development of deep-learning (DL) models aimed at supporting pathologists in their daily work and improving patient care. However, the clinical adoption of such ...

ORAKLE: Optimal Risk prediction for mAke30 in patients with sepsis associated AKI using deep LEarning.

Critical care (London, England)
BACKGROUND: Major Adverse Kidney Events within 30 days (MAKE30) is an important patient-centered outcome for assessing the impact of acute kidney injury (AKI). Existing prediction models for MAKE30 are static and overlook dynamic changes in clinical ...

A comparative analysis of deep learning models for assisting in the diagnosis of periapical lesions in periapical radiographs.

BMC oral health
PURPOSE: Numerous studies have investigated the use of convolutional neural network (CNN) models for detecting periapical lesions(PLs). However, limited research has focused on evaluating their potential in assisting clinicians with diagnosis. This s...

Evolution of deep learning tooth segmentation from CT/CBCT images: a systematic review and meta-analysis.

BMC oral health
BACKGROUND: Deep learning has been utilized to segment teeth from computed tomography (CT) or cone-beam CT (CBCT). However, the performance of deep learning is unknown due to multiple models and diverse evaluation metrics. This systematic review and ...

A novel MRI-based deep learning imaging biomarker for comprehensive assessment of the lenticulostriate artery-neural complex.

BMC medical imaging
OBJECTIVES: To develop a deep learning network for extracting features from the blood-supplying regions of the lenticulostriate artery (LSA) and to establish these features as an imaging biomarker for the comprehensive assessment of the lenticulostri...

Prediction of one-year recurrence among breast cancer patients undergone surgery using artificial intelligence-based algorithms: a retrospective study on prognostic factors.

BMC cancer
BACKGROUND AND AIM: Breast cancer is highly prevalent, with an increasing trend in women globally. Although the survival of breast cancer is relatively high, the recurrence rate is also high, demanding effective predictive solutions to breast cancer ...

Detecting microcephaly and macrocephaly from ultrasound images using artificial intelligence.

BMC medical imaging
BACKGROUND: Microcephaly and macrocephaly, which are abnormal congenital markers, are associated with developmental and neurologic deficits. Hence, there is a medically imperative need to conduct ultrasound imaging early on. However, resource-limited...