AIMC Topic: Deep Learning

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A realistic fish-habitat dataset to evaluate algorithms for underwater visual analysis.

Scientific reports
Visual analysis of complex fish habitats is an important step towards sustainable fisheries for human consumption and environmental protection. Deep Learning methods have shown great promise for scene analysis when trained on large-scale datasets. Ho...

Ultra-low-dose chest CT imaging of COVID-19 patients using a deep residual neural network.

European radiology
OBJECTIVES: The current study aimed to design an ultra-low-dose CT examination protocol using a deep learning approach suitable for clinical diagnosis of COVID-19 patients.

High throughput assessment of biomarkers in tissue microarrays using artificial intelligence: PTEN loss as a proof-of-principle in multi-center prostate cancer cohorts.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Phosphatase and tensin homolog (PTEN) loss is associated with adverse outcomes in prostate cancer and has clinical potential as a prognostic biomarker. The objective of this work was to develop an artificial intelligence (AI) system for automated det...

Transcranial MR Imaging-Guided Focused Ultrasound Interventions Using Deep Learning Synthesized CT.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Transcranial MR imaging-guided focused ultrasound is a promising novel technique to treat multiple disorders and diseases. Planning for transcranial MR imaging-guided focused ultrasound requires both a CT scan for skull densit...

A deep learning approach for facility patient attendance prediction based on medical booking data.

Scientific reports
Nowadays, data-driven methodologies based on the clinical history of patients represent a promising research field in which personalized and intelligent healthcare systems can be opportunely designed and developed. In this perspective, Machine Learni...

Effect of sequence padding on the performance of deep learning models in archaeal protein functional prediction.

Scientific reports
The use of raw amino acid sequences as input for deep learning models for protein functional prediction has gained popularity in recent years. This scheme obliges to manage proteins with different lengths, while deep learning models require same-shap...

T1 and T2 MR fingerprinting measurements of prostate cancer and prostatitis correlate with deep learning-derived estimates of epithelium, lumen, and stromal composition on corresponding whole mount histopathology.

European radiology
OBJECTIVES: To explore the associations between T1 and T2 magnetic resonance fingerprinting (MRF) measurements and corresponding tissue compartment ratios (TCRs) on whole mount histopathology of prostate cancer (PCa) and prostatitis.

Adverse drug event detection using reason assignments in FDA drug labels.

Journal of biomedical informatics
Adverse drug events (ADEs) are unintended incidents that involve the taking of a medication. ADEs pose significant health and financial problems worldwide. Information about ADEs can inform health care and improve patient safety. However, much of thi...

Active Learning Plus Deep Learning Can Establish Cost-Effective and Robust Model for Multichannel Image: A Case on Hyperspectral Image Classification.

Sensors (Basel, Switzerland)
Relying on large scale labeled datasets, deep learning has achieved good performance in image classification tasks. In agricultural and biological engineering, image annotation is time-consuming and expensive. It also requires annotators to have tech...

A deep learning approach in diagnosing fungal keratitis based on corneal photographs.

Scientific reports
Fungal keratitis (FK) is the most devastating and vision-threatening microbial keratitis, but clinical diagnosis a great challenge. This study aimed to develop and verify a deep learning (DL)-based corneal photograph model for diagnosing FK. Corneal ...