AIMC Topic: Deep Learning

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Deep learning for diffusion in porous media.

Scientific reports
We adopt convolutional neural networks (CNN) to predict the basic properties of the porous media. Two different media types are considered: one mimics the sand packings, and the other mimics the systems derived from the extracellular space of biologi...

Deep learning to automatically evaluate HER2 gene amplification status from fluorescence in situ hybridization images.

Scientific reports
Human epidermal growth factor receptor 2 (HER2) gene amplification helps identify breast cancer patients who may respond to targeted anti-HER2 therapy. This study aims to develop an automated method for quantifying HER2 fluorescence in situ hybridiza...

Detecting common coccinellids found in sorghum using deep learning models.

Scientific reports
Increased global production of sorghum has the potential to meet many of the demands of a growing human population. Developing automation technologies for field scouting is crucial for long-term and low-cost production. Since 2013, sugarcane aphid (S...

Infection diagnosis in hydrocephalus CT images: a domain enriched attention learning approach.

Journal of neural engineering
. Hydrocephalus is the leading indication for pediatric neurosurgical care worldwide. Identification of postinfectious hydrocephalus (PIH) verses non-postinfectious hydrocephalus, as well as the pathogen involved in PIH is crucial for developing an a...

A Hybrid Deep Learning Approach to Identify Preventable Childhood Hearing Loss.

Ear and hearing
OBJECTIVE: Childhood hearing loss has well-known, lifelong consequences. Infection-related hearing loss disproportionately affects underserved communities yet can be prevented with early identification and treatment. This study evaluates the utility ...

Two-stage multi-task deep learning framework for simultaneous pelvic bone segmentation and landmark detection from CT images.

International journal of computer assisted radiology and surgery
PURPOSE: Pelvic bone segmentation and landmark definition from computed tomography (CT) images are prerequisite steps for the preoperative planning of total hip arthroplasty. In clinical applications, the diseased pelvic anatomy usually degrades the ...

External validation of a deep learning detection system for glaucomatous optic neuropathy: a real-world multicentre study.

Eye (London, England)
OBJECTIVES: To conduct an external validation of an automated artificial intelligence (AI) diagnostic system using fundus photographs from a real-life multicentre cohort.

The promise of explainable deep learning for omics data analysis: Adding new discovery tools to AI.

New biotechnology
Deep learning has already revolutionised the way a wide range of data is processed in many areas of daily life. The ability to learn abstractions and relationships from heterogeneous data has provided impressively accurate prediction and classificati...

Interpretable HER2 scoring by evaluating clinical guidelines through a weakly supervised, constrained deep learning approach.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The evaluation of the Human Epidermal growth factor Receptor-2 (HER2) expression is an important prognostic biomarker for breast cancer treatment selection. However, HER2 scoring has notoriously high interobserver variability due to stain variations ...

Pulmonary contusion: automated deep learning-based quantitative visualization.

Emergency radiology
PURPOSE: Rapid automated CT volumetry of pulmonary contusion may predict progression to Acute Respiratory Distress Syndrome (ARDS) and help guide early clinical management in at-risk trauma patients. This study aims to train and validate state-of-the...