AIMC Topic: Humans

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DCT-MIL: Deep CNN transferred multiple instance learning for COPD identification using CT images.

Physics in medicine and biology
While many pre-defined computed tomographic (CT) measures have been utilized to characterize chronic obstructive pulmonary disease (COPD), it is still challenging to represent pathological alternations of multiple dimensions and highly spatial hetero...

A Review of Deep Learning for Screening, Diagnosis, and Detection of Glaucoma Progression.

Translational vision science & technology
UNLABELLED: Because of recent advances in computing technology and the availability of large datasets, deep learning has risen to the forefront of artificial intelligence, with performances that often equal, or sometimes even exceed, those of human s...

Research of Epidemic Big Data Based on Improved Deep Convolutional Neural Network.

Computational and mathematical methods in medicine
In recent years, with the acceleration of the aging process and the aggravation of life pressure, the proportion of chronic epidemics has gradually increased. A large amount of medical data will be generated during the hospitalization of diabetics. I...

Computational Cytology: Lessons Learned from Pap Test Computer-Assisted Screening.

Acta cytologica
BACKGROUND: In the face of rapid technological advances in computational cytology including artificial intelligence (AI), optimization of its application to clinical practice would benefit from reflection on the lessons learned from the decades-long ...

Diffusion Histology Imaging Combining Diffusion Basis Spectrum Imaging (DBSI) and Machine Learning Improves Detection and Classification of Glioblastoma Pathology.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Glioblastoma (GBM) is one of the deadliest cancers with no cure. While conventional MRI has been widely adopted to examine GBM clinically, accurate neuroimaging assessment of tumor histopathology for improved diagnosis, surgical planning, an...

Deep-COVID: Predicting COVID-19 from chest X-ray images using deep transfer learning.

Medical image analysis
The COVID-19 pandemic is causing a major outbreak in more than 150 countries around the world, having a severe impact on the health and life of many people globally. One of the crucial step in fighting COVID-19 is the ability to detect the infected p...

Attention-Enriched Deep Learning Model for Breast Tumor Segmentation in Ultrasound Images.

Ultrasound in medicine & biology
Incorporating human domain knowledge for breast tumor diagnosis is challenging because shape, boundary, curvature, intensity or other common medical priors vary significantly across patients and cannot be employed. This work proposes a new approach t...

Radiogenomics for predicting p53 status, PD-L1 expression, and prognosis with machine learning in pancreatic cancer.

British journal of cancer
BACKGROUND: Radiogenomics is an emerging field that integrates "Radiomics" and "Genomics". In the current study, we aimed to predict the genetic information of pancreatic tumours in a simple, inexpensive, and non-invasive manner, using cancer imaging...

Automatic skin lesion classification based on mid-level feature learning.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Dermoscopic images are widely used for melanoma detection. Many existing works based on traditional classification methods and deep learning models have been proposed for automatic skin lesion analysis. The traditional classification methods use hand...