AIMC Topic: Deep Learning

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Deep learning with noisy labels in medical prediction problems: a scoping review.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Medical research faces substantial challenges from noisy labels attributed to factors like inter-expert variability and machine-extracted labels. Despite this, the adoption of label noise management remains limited, and label noise is lar...

Streamlining social media information retrieval for public health research with deep learning.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Social media-based public health research is crucial for epidemic surveillance, but most studies identify relevant corpora with keyword-matching. This study develops a system to streamline the process of curating colloquial medical diction...

Improved stent sharpness evaluation with super-resolution deep learning reconstruction in coronary CT angiography.

The British journal of radiology
OBJECTIVES: This study aimed to assess the impact of super-resolution deep learning reconstruction (SR-DLR) on coronary CT angiography (CCTA) image quality and blooming artifacts from coronary artery stents in comparison to conventional methods, incl...

[Artificial intelligence research advances in discrimination and diagnosis of pulmonary ground-glass nodules].

Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases
Lung cancer, which accounts for about 18% of all cancer-related deaths worldwide, has a dismal 5-year survival rate of less than 20%. Survival rates for early-stage lung cancers (stages IA1, IA2, IA3, and IB, according to the TNM staging system) are ...

Is Learning in Biological Neural Networks Based on Stochastic Gradient Descent? An Analysis Using Stochastic Processes.

Neural computation
In recent years, there has been an intense debate about how learning in biological neural networks (BNNs) differs from learning in artificial neural networks. It is often argued that the updating of connections in the brain relies only on local infor...

Deep learning to detect left ventricular structural abnormalities in chest X-rays.

European heart journal
BACKGROUND AND AIMS: Early identification of cardiac structural abnormalities indicative of heart failure is crucial to improving patient outcomes. Chest X-rays (CXRs) are routinely conducted on a broad population of patients, presenting an opportuni...

The cytoarchitectonic landscape revealed by deep learning method facilitated precise positioning in mouse neocortex.

Cerebral cortex (New York, N.Y. : 1991)
Neocortex is a complex structure with different cortical sublayers and regions. However, the precise positioning of cortical regions can be challenging due to the absence of distinct landmarks without special preparation. To address this challenge, w...

How Artificial Intelligence Unravels the Complex Web of Cancer Drug Response.

Cancer research
The intersection of precision medicine and artificial intelligence (AI) holds profound implications for cancer treatment, with the potential to significantly advance our understanding of drug responses based on the intricate architecture of tumor cel...

Mathematical Model-Driven Deep Learning Enables Personalized Adaptive Therapy.

Cancer research
UNLABELLED: Standard-of-care treatment regimens have long been designed for maximal cell killing, yet these strategies often fail when applied to metastatic cancers due to the emergence of drug resistance. Adaptive treatment strategies have been deve...