AIMC Topic: Humans

Aiming at serving the interdisciplinary demand in network science, this paper introduces a new concept for complex networks, named network stiffness, which is extracted from structural engineering by assuming that a complex network behaves similarly ...

BACKGROUND: Handheld laparoscopic robotized instruments have been developed to combine the advantages of a robotic operation system and conventional laparoscopic instruments. Direct objective standards are needed to quantify surgeons' skill level and...

Many classical machine learning techniques have been used to explore Alzheimer's disease (AD), evolving from image decomposition techniques such as principal component analysis toward higher complexity, non-linear decomposition algorithms. With the a...

Magnetic resonance (MR) images denoising is important in medical image analysis. Denoising methods based on deep learning have shown great promise and outperform all of the other conventional methods. However, deep-learning methods are limited by the...

BACKGROUND: Driven by the recent ubiquity of big data and computing power, we established the Machine Learning Arthroplasty Laboratory (MLAL) to examine and apply artificial intelligence (AI) to musculoskeletal medicine.

BACKGROUND AND OBJECTIVE: The leading cause of vision loss in the Western World is Age-related Macular Degeneration (AMD), but together with modern medicines, tracking the number of Hyperreflective Foci (HF) on Optical Coherence Tomography (OCT) imag...

Influenza type A, a serious infectious disease of the human respiratory tract, poses an enormous threat to human health worldwide. It leads to high mortality rates in poultry, pigs, and humans. The primary target identity regions for the human immune...

We propose a novel framework for classification of mitotic v/s non-mitotic cells in a Computer Aided Diagnosis (CAD) system for Anti-Nuclear Antibodies (ANA) detection. In the proposed work, due to unique characteristics (the rare occurrence) of the ...