OMGMed: Advanced System for Ocular Myasthenia Gravis Diagnosis via Eye Image Segmentation.

This paper presents an eye image segmentation-based computer-aided system for automatic diagnosis of ocular myasthenia gravis (OMG), called OMGMed. It provides great potential to effectively liberate the diagnostic efficiency of expert doctors (the scarce resources) and reduces the cost of healthcare treatment for diagnosed patients, making it possible to disseminate high-quality myasthenia gravis healthcare to under-developed areas. The system is composed of data pre-processing, indicator calculation, and automatic OMG scoring.

A Comprehensive Review on Synergy of Multi-Modal Data and AI Technologies in Medical Diagnosis.

Disease diagnosis represents a critical and arduous endeavor within the medical field. Artificial intelligence (AI) techniques, spanning from machine learning and deep learning to large model paradigms, stand poised to significantly augment physicians in rendering more evidence-based decisions, thus presenting a pioneering solution for clinical practice. Traditionally, the amalgamation of diverse medical data modalities (e.

Detection and Classification of Bronchiectasis Based on Improved Mask-RCNN.

Bronchiectasis is defined as a permanent dilation of the bronchi that can cause pulmonary ventilation dysfunction. CT examination is an important means of diagnosing bronchiectasis. It can also be used in severity scoring.

Performance of deep neural network-based artificial intelligence method in diabetic retinopathy screening: a systematic review and meta-analysis of diagnostic test accuracy.

Objective: Automatic diabetic retinopathy screening system based on neural networks has been used to detect diabetic retinopathy (DR). However, there is no quantitative synthesis of performance of these methods. We aimed to estimate the sensitivity and specificity of neural networks in DR grading.

An Investigation about Gene Modules Associated with hDPSC Differentiation for Adolescents.

Dental pulp stem cells (DPSCs) have the property of self-renewal and multidirectional differentiation so that they have the potential for future regenerative therapy of various diseases. The latest breakthrough in the biology of stem cells and the development of regenerative biology provides an effective strategy for regenerative therapy. However, in the medium promoting differentiation during long-term passage, DPSCs would lose their differentiation capability.

Development of a computer-aided tool for the pattern recognition of facial features in diagnosing Turner syndrome: comparison of diagnostic accuracy with clinical workers.

Technologies applied for the recognition of facial features in diagnosing certain disorders seem to be promising in reducing the medical burden and improve the efficiency. This pilot study aimed to develop a computer-assisted tool for the pattern recognition of facial features for diagnosing Turner syndrome (TS). Photographs of 54 patients with TS and 158 female controls were collected from July 2016 to May 2017.

The effect of interaction between EtOH dosage and exposure time on gene expression in DPSC.

Alcohol (EtOH) dosage and exposure time can affect gene expression. However, whether there exists synergistic effect is unknown. Here, we analyzed the hDPSC gene microarray dataset GSE57255 downloaded from Gene Expression Omnibus and found that the interaction between EtOH dosage and exposure time on gene expression are statistically significant for two probes: 201917_s_at near gene SLC25A36 and 217649_at near gene ZFAND5.

Application of Weighted Gene Co-expression Network Analysis for Data from Paired Design.

Investigating how genes jointly affect complex human diseases is important, yet challenging. The network approach (e.g.

Coordinated Digital-Assisted Program Improved Door-to-Balloon Time for Acute Chest Pain Patients.

Emergency care for patients with chest pain can be a challenge in remote areas. Digital communication technology has the potential to improve outcomes by allowing early diagnosis and faster treatment. The aim of the present study was to investigate whether implementation of a coordinated digital-assisted program (CDAP) for Chinese hospitals can reduce the door-to-balloon (D2B) time for percutaneous coronary intervention (PCI) in acute chest pain patients in China.

Exploiting ensemble learning for automatic cataract detection and grading.

Cataract is defined as a lenticular opacity presenting usually with poor visual acuity. It is one of the most common causes of visual impairment worldwide. Early diagnosis demands the expertise of trained healthcare professionals, which may present a barrier to early intervention due to underlying costs.