AIMC Topic: Humans

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Multi-scale supervised clustering-based feature selection for tumor classification and identification of biomarkers and targets on genomic data.

BMC genomics
BACKGROUND: The small number of samples and the curse of dimensionality hamper the better application of deep learning techniques for disease classification. Additionally, the performance of clustering-based feature selection algorithms is still far ...

Alcoholic liver disease: A registry view on comorbidities and disease prediction.

PLoS computational biology
Alcoholic-related liver disease (ALD) is the cause of more than half of all liver-related deaths. Sustained excess drinking causes fatty liver and alcohol-related steatohepatitis, which may progress to alcoholic liver fibrosis (ALF) and eventually to...

A machine learning algorithm to increase COVID-19 inpatient diagnostic capacity.

PloS one
Worldwide, testing capacity for SARS-CoV-2 is limited and bottlenecks in the scale up of polymerase chain reaction (PCR-based testing exist. Our aim was to develop and evaluate a machine learning algorithm to diagnose COVID-19 in the inpatient settin...

Population demographics in geographic proximity to hospitals with robotic platforms do not correlate with disparities in access to robotic surgery.

Surgical endoscopy
BACKGROUND: Disparities in access to robotic surgery have been shown on the local, regional, and national level. This study aims to see if the location of hospitals with robotic platforms (HWR) correlates with population trends to explain the dispari...

Classification of normal sinus rhythm, abnormal arrhythmia and congestive heart failure ECG signals using LSTM and hybrid CNN-SVM deep neural networks.

Computer methods in biomechanics and biomedical engineering
Effective monitoring of heart patients according to heart signals can save a huge amount of life. In the last decade, the classification and prediction of heart diseases according to ECG signals has gained great importance for patients and doctors. I...

Open versus robot-assisted partial nephrectomy: A longitudinal comparison of 880 patients over 10 years.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Most comparisons between robot-assisted partial nephrectomy (RAPN) and open partial nephrectomy (OPN) indicate the superiority of RAPN, but the learning curve is often not considered.

Approximating anatomically-guided PET reconstruction in image space using a convolutional neural network.

NeuroImage
In the last two decades, it has been shown that anatomically-guided PET reconstruction can lead to improved bias-noise characteristics in brain PET imaging. However, despite promising results in simulations and first studies, anatomically-guided PET ...

Microscopic brain tumor detection and classification using 3D CNN and feature selection architecture.

Microscopy research and technique
Brain tumor is one of the most dreadful natures of cancer and caused a huge number of deaths among kids and adults from the past few years. According to WHO standard, the 700,000 humans are being with a brain tumor and around 86,000 are diagnosed sin...

Deep Learning to Estimate RECIST in Patients with NSCLC Treated with PD-1 Blockade.

Cancer discovery
Real-world evidence (RWE), conclusions derived from analysis of patients not treated in clinical trials, is increasingly recognized as an opportunity for discovery, to reduce disparities, and to contribute to regulatory approval. Maximal value of RWE...

Multi-label zero-shot learning with graph convolutional networks.

Neural networks : the official journal of the International Neural Network Society
The goal of zero-shot learning (ZSL) is to build a classifier that recognizes novel categories with no corresponding annotated training data. The typical routine is to transfer knowledge from seen classes to unseen ones by learning a visual-semantic ...