AIMC Topic: Deep Learning

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ECMWF short-term prediction accuracy improvement by deep learning.

Scientific reports
This paper aims to describe and evaluate the proposed calibration model based on a neural network for post-processing of two essential meteorological parameters, namely near-surface air temperature (2 m) and 24 h accumulated precipitation. The main i...

A deep learning based method for intelligent detection of seafarers' mental health condition.

Scientific reports
Mental health monitoring of seafarers is an important part of achieving normal development of the ocean shipping industry. In this paper, a dual subjective-objective testing scheme is proposed to achieve a more effective and intelligent assessment of...

Real-time automatic prediction of treatment response to transcatheter arterial chemoembolization in patients with hepatocellular carcinoma using deep learning based on digital subtraction angiography videos.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Transcatheter arterial chemoembolization (TACE) is the mainstay of therapy for intermediate-stage hepatocellular carcinoma (HCC); yet its efficacy varies between patients with the same tumor stage. Accurate prediction of TACE response rem...

Prediction of lung cancer using gene expression and deep learning with KL divergence gene selection.

BMC bioinformatics
BACKGROUND: Lung cancer is one of the cancers with the highest mortality rate in China. With the rapid development of high-throughput sequencing technology and the research and application of deep learning methods in recent years, deep neural network...

Deep Learning for Automatic Upper Airway Obstruction Detection by Analysis of Flow-Volume Curve.

Respiration; international review of thoracic diseases
BACKGROUND: Due to the similar symptoms of upper airway obstruction to asthma, misdiagnosis is common. Spirometry is a cost-effective screening test for upper airway obstruction and its characteristic patterns involving fixed, variable intrathoracic ...

A lightweight CNN-based network on COVID-19 detection using X-ray and CT images.

Computers in biology and medicine
BACKGROUND AND OBJECTIVES: The traditional method of detecting COVID-19 disease mainly rely on the interpretation of computer tomography (CT) or X-ray images (X-ray) by doctors or professional researchers to identify whether it is COVID-19 disease, w...

A computer-aided diagnosis system for detecting various diabetic retinopathy grades based on a hybrid deep learning technique.

Medical & biological engineering & computing
Diabetic retinopathy (DR) is a serious disease that may cause vision loss unawares without any alarm. Therefore, it is essential to scan and audit the DR progress continuously. In this respect, deep learning techniques achieved great success in medic...

Toward automatic beam angle selection for pencil-beam scanning proton liver treatments: A deep learning-based approach.

Medical physics
BACKGROUND: Dose deposition characteristics of proton radiation can be advantageous over photons. Proton treatment planning, however, poses additional challenges for the planners. Proton therapy is usually delivered with only a small number of beam a...

Medical deep learning-A systematic meta-review.

Computer methods and programs in biomedicine
Deep learning has remarkably impacted several different scientific disciplines over the last few years. For example, in image processing and analysis, deep learning algorithms were able to outperform other cutting-edge methods. Additionally, deep lea...

AI recognition of patient race in medical imaging: a modelling study.

The Lancet. Digital health
BACKGROUND: Previous studies in medical imaging have shown disparate abilities of artificial intelligence (AI) to detect a person's race, yet there is no known correlation for race on medical imaging that would be obvious to human experts when interp...