AIMC Topic: Humans

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Brain-guided manifold transferring to improve the performance of spiking neural networks in image classification.

Journal of computational neuroscience
Spiking neural networks (SNNs), as the third generation of neural networks, are based on biological models of human brain neurons. In this work, a shallow SNN plays the role of an explicit image decoder in the image classification. An LSTM-based EEG ...

Robot-assisted fluorescent sentinel lymph node identification in early-stage colon cancer.

Surgical endoscopy
BACKGROUND: Patients with cT1-2 colon cancer (CC) have a 10-20% risk of lymph node metastases. Sentinel lymph node identification (SLNi) could improve staging and reduce morbidity in future organ-preserving CC surgery. This pilot study aimed to asses...

Cost-effectiveness analysis of robot-assisted laparoscopic surgery for complex pediatric surgical conditions.

Surgical endoscopy
BACKGROUND: Robotics has been used safely and successfully in a variety of adult surgeries and is gradually gaining ground in pediatrics. While the benefits of robotic-assisted surgery in disease treatment are well recognized, its high cost has led t...

Aortic Annulus Detection Based on Deep Learning for Transcatheter Aortic Valve Replacement Using Cardiac Computed Tomography.

Journal of Korean medical science
BACKGROUND: To propose a deep learning architecture for automatically detecting the complex structure of the aortic annulus plane using cardiac computed tomography (CT) for transcatheter aortic valve replacement (TAVR).

CT-based deep learning radiomics nomogram for the prediction of pathological grade in bladder cancer: a multicenter study.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: To construct and assess a computed tomography (CT)-based deep learning radiomics nomogram (DLRN) for predicting the pathological grade of bladder cancer (BCa) preoperatively.

Perioperative safety and efficacy of robot-assisted total hip arthroplasty in ERAS-managed patients: a pilot study.

Journal of orthopaedic surgery and research
AIMS: Robot-assisted total hip arthroplasty (rTHA) boasts superior accuracy in implant placement, but there is a lack of effective assessment in perioperative management in the context of enhanced recovery after surgery (ERAS). This study aimed to co...

An unsupervised deep learning framework for predicting human essential genes from population and functional genomic data.

BMC bioinformatics
BACKGROUND: The ability to accurately predict essential genes intolerant to loss-of-function (LOF) mutations can dramatically improve the identification of disease-associated genes. Recently, there have been numerous computational methods developed t...

A GPU-based computational framework that bridges neuron simulation and artificial intelligence.

Nature communications
Biophysically detailed multi-compartment models are powerful tools to explore computational principles of the brain and also serve as a theoretical framework to generate algorithms for artificial intelligence (AI) systems. However, the expensive comp...

Region of interest focused MRI to synthetic CT translation using regression and segmentation multi-task network.

Physics in medicine and biology
. In MR-only clinical workflow, replacing CT with MR image is of advantage for workflow efficiency and reduces radiation to the patient. An important step required to eliminate CT scan from the workflow is to generate the information provided by CT v...

Application of machine learning and artificial intelligence in the diagnosis and classification of polycystic ovarian syndrome: a systematic review.

Frontiers in endocrinology
INTRODUCTION: Polycystic Ovarian Syndrome (PCOS) is the most common endocrinopathy in women of reproductive age and remains widely underdiagnosed leading to significant morbidity. Artificial intelligence (AI) and machine learning (ML) hold promise in...