AIMC Topic: Humans

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Understanding How CNNs Recognize Facial Expressions: A Case Study with LIME and CEM.

Sensors (Basel, Switzerland)
Recognizing facial expressions has been a persistent goal in the scientific community. Since the rise of artificial intelligence, convolutional neural networks (CNN) have become popular to recognize facial expressions, as images can be directly used ...

Reinforcement learning using Deep networks and learning accurately localizes brain tumors on MRI with very small training sets.

BMC medical imaging
BACKGROUND: Supervised deep learning in radiology suffers from notorious inherent limitations: 1) It requires large, hand-annotated data sets; (2) It is non-generalizable; and (3) It lacks explainability and intuition. It has recently been proposed t...

Machine learning-based techniques to improve lung transplantation outcomes and complications: a systematic review.

BMC medical research methodology
BACKGROUND: Machine learning has been used to develop predictive models to support clinicians in making better and more reliable decisions. The high volume of collected data in the lung transplant process makes it possible to extract hidden patterns ...

Deep learning-based 3D OCT imaging for detection of lamina cribrosa defects in eyes with high myopia.

Scientific reports
The lamina cribrosa (LC) is a collagenous tissue located in the optic nerve head, and its dissection is observed in eyes with pathologic myopia as a LC defect (LCD). The diagnosis of LCD has been difficult because the LC is located deep beneath the r...

Electron energy loss spectroscopy database synthesis and automation of core-loss edge recognition by deep-learning neural networks.

Scientific reports
The ionization edges encoded in the electron energy loss spectroscopy (EELS) spectra enable advanced material analysis including composition analyses and elemental quantifications. The development of the parallel EELS instrument and fast, sensitive d...

Combined robot motor assistance with neural circuit-based virtual reality (NeuCir-VR) lower extremity rehabilitation training in patients after stroke: a study protocol for a single-centre randomised controlled trial.

BMJ open
INTRODUCTION: Improving lower extremity motor function is the focus and difficulty of post-stroke rehabilitation treatment. More recently, robot-assisted and virtual reality (VR) training are commonly used in post-stroke rehabilitation and are consid...

Examining the Use of an Artificial Intelligence Model to Diagnose Influenza: Development and Validation Study.

Journal of medical Internet research
BACKGROUND: The global burden of influenza is substantial. It is a major disease that causes annual epidemics and occasionally, pandemics. Given that influenza primarily infects the upper respiratory system, it may be possible to diagnose influenza i...

A deep-learning model for transforming the style of tissue images from cryosectioned to formalin-fixed and paraffin-embedded.

Nature biomedical engineering
Histological artefacts in cryosectioned tissue can hinder rapid diagnostic assessments during surgery. Formalin-fixed and paraffin-embedded (FFPE) tissue provides higher quality slides, but the process for obtaining them is laborious (typically lasti...

The efficiency of artificial intelligence methods for finding radiographic features in different endodontic treatments - a systematic review.

Acta odontologica Scandinavica
OBJECTIVES: To assess the efficiency of AI methods in finding radiographic features in Endodontic treatment considerations.