AIMC Topic: Humans

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Re-evaluation of possible vulnerable sites in the lateral pelvic cavity to local recurrence during robot-assisted total mesorectal excision.

Surgical endoscopy
BACKGROUND: Despite mechanical and technical improvements in laparoscopic and robot-assisted (LAR) rectal cancer procedures, the absence of prognostic disparities among various approaches cannot improve the quality of TME. The present study re-evalua...

Artificial Intelligence System to Determine Risk of T1 Colorectal Cancer Metastasis to Lymph Node.

Gastroenterology
BACKGROUND & AIMS: In accordance with guidelines, most patients with T1 colorectal cancers (CRC) undergo surgical resection with lymph node dissection, despite the low incidence (∼10%) of metastasis to lymph nodes. To reduce unnecessary surgical rese...

Transfer learning in deep neural network based under-sampled MR image reconstruction.

Magnetic resonance imaging
In Magnetic Resonance Imaging (MRI), the success of deep learning-based under-sampled MR image reconstruction depends on: (i) size of the training dataset, (ii) generalization capabilities of the trained neural network. Whenever there is a mismatch b...

Diagnosis of Coronavirus Disease 2019 Pneumonia by Using Chest Radiography: Value of Artificial Intelligence.

Radiology
Background Radiologists are proficient in differentiating between chest radiographs with and without symptoms of pneumonia but have found it more challenging to differentiate coronavirus disease 2019 (COVID-19) pneumonia from non-COVID-19 pneumonia o...

A deep learning network-assisted bladder tumour recognition under cystoscopy based on Caffe deep learning framework and EasyDL platform.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Cystoscopy plays an important role in the diagnosis of bladder tumours. As a typical representative of the deep learning algorithm, the convolutional neural network has shown great advantages in the field of image recognition and segmenta...

Virus identification in electron microscopy images by residual mixed attention network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Virus identification in electron microscopy (EM) images is considered as one of the front-line method in pathogen diagnosis and re-emerging infectious agents. However, the existing methods either focused on the detection of ...

Evolutionary artificial intelligence based peptide discoveries for effective Covid-19 therapeutics.

Biochimica et biophysica acta. Molecular basis of disease
An epidemic caused by COVID-19 in China turned into pandemic within a short duration affecting countries worldwide. Researchers and companies around the world are working on all the possible strategies to develop a curative or preventive strategy for...

Learning patterns of the ageing brain in MRI using deep convolutional networks.

NeuroImage
Both normal ageing and neurodegenerative diseases cause morphological changes to the brain. Age-related brain changes are subtle, nonlinear, and spatially and temporally heterogenous, both within a subject and across a population. Machine learning mo...

Patient generated health data and electronic health record integration in oncologic surgery: A call for artificial intelligence and machine learning.

Journal of surgical oncology
In this review, we aim to assess the current state of science in relation to the integration of patient-generated health data (PGHD) and patient-reported outcomes (PROs) into routine clinical care with a focus on surgical oncology populations. We wil...