AIMC Topic: Deep Learning

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Decoding the impact of neighboring amino acids on ESI-MS intensity output through deep learning.

Journal of proteomics
Peptide-level quantification using mass spectrometry (MS) is no trivial task as the physicochemical properties affect both response and detectability. The specific amino acid (AA) sequence affects these properties, however the connection between sequ...

Multifunctional Human-Computer Interaction System Based on Deep Learning-Assisted Strain Sensing Array.

ACS applied materials & interfaces
Continuous and reliable monitoring of gait is crucial for health monitoring, such as postoperative recovery of bone joint surgery and early diagnosis of disease. However, existing gait analysis systems often suffer from large volumes and the requirem...

SSCI: Self-Supervised Deep Learning Improves Network Structure for Cancer Driver Gene Identification.

International journal of molecular sciences
The pathogenesis of cancer is complex, involving abnormalities in some genes in organisms. Accurately identifying cancer genes is crucial for the early detection of cancer and personalized treatment, among other applications. Recent studies have used...

Deep residual 2D convolutional neural network for cardiovascular disease classification.

Scientific reports
Cardiovascular disease (CVD) continues to be a major global health concern, underscoring the need for advancements in medical care. The use of electrocardiograms (ECGs) is crucial for diagnosing cardiac conditions. However, the reliance on profession...

Controlled and Real-Life Investigation of Optical Tracking Sensors in Smart Glasses for Monitoring Eating Behavior Using Deep Learning: Cross-Sectional Study.

JMIR mHealth and uHealth
BACKGROUND: The increasing prevalence of obesity necessitates innovative approaches to better understand this health crisis, particularly given its strong connection to chronic diseases such as diabetes, cancer, and cardiovascular conditions. Monitor...

Real-world application of a 3D deep learning model for detecting and localizing cerebral microbleeds.

Acta neurochirurgica
BACKGROUND: Detection and localization of cerebral microbleeds (CMBs) is crucial for disease diagnosis and treatment planning. However, CMB detection is labor-intensive, time-consuming, and challenging owing to its visual similarity to mimics. This s...

Guide for the application of the data augmentation approach on sets of texts in Spanish for sentiment and emotion analysis.

PloS one
Over the last ten years, social media has become a crucial data source for businesses and researchers, providing a space where people can express their opinions and emotions. To analyze this data and classify emotions and their polarity in texts, nat...

BSNEU-net: Block Feature Map Distortion and Switchable Normalization-Based Enhanced Union-net for Acute Leukemia Detection on Heterogeneous Dataset.

Journal of imaging informatics in medicine
Acute leukemia is characterized by the swift proliferation of immature white blood cells (WBC) in the blood and bone marrow. It is categorized into acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML), depending on whether the cell-lin...

Automatic Segmentation of Ultrasound-Guided Quadratus Lumborum Blocks Based on Artificial Intelligence.

Journal of imaging informatics in medicine
Ultrasound-guided quadratus lumborum block (QLB) technology has become a widely used perioperative analgesia method during abdominal and pelvic surgeries. Due to the anatomical complexity and individual variability of the quadratus lumborum muscle (Q...

Deep learning in Cobb angle automated measurement on X-rays: a systematic review and meta-analysis.

Spine deformity
PURPOSE: This study aims to provide an overview of different deep learning algorithms (DLAs), identify the limitations, and summarize potential solutions to improve the performance of DLAs.