Journal of Artificial Intelligence for Medical Sciences

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15 articles
Review Article

Influence of Gut Microbiota on Mental Health via Neurotransmitters: A Review

Ting Liu, K. Anton Feenstra, Jaap Heringa, Zhisheng Huang
Pages: 1 - 14
Mental disorders related to the imbalance of neurotransmitters, which are substantially affected by gut microbiota. Gut microbiota impacts on mental health by regulating the level of neurotransmitters in the host. To understand the influence of gut microbiota on mental health via neurotransmitters, we...
Review Article

Deep Learning Methodologies for Genomic Data Prediction: Review

Yusuf Aleshinloye Abass, Steve A. Adeshina
Pages: 1 - 11
The last few years have seen an advancement in genomic research in bioinformatics. With the introduction of high-throughput sequencing techniques, researchers now can analyze and produce a large amount of genomic datasets and this has aided the classification of genomic studies as a “big data” discipline....
Research Article

Ensembled Deep Neural Network for Intracranial Hemorrhage Detection and Subtype Classification on Noncontrast CT Images

Yunan Wu, Mark P. Supanich, Jie Deng
Pages: 12 - 20
Rapid and accurate diagnosis of intracranial hemorrhage is clinically significant to ensure timely treatment. In this study, we developed an ensembled deep neural network for the detection and subtype classification of intracranial hemorrhage. The model consisted of two parallel network pathways, one...
Research Article

Research on Construction of Knowledge Graph of Intestinal Cells

Fengfeng He, Ling Zhang, Wei Qu, Chong Teng, Dan Xie
Pages: 15 - 22
Intestinal cells play a significant role in human physiological metabolism, immune protection, and development and control of nervous system diseases. With the flourishing development of artificial intelligence technology and arrival of intestinal cellular research enthusiasm, how to obtain knowledge...
Research Article

TMRGM: A Template-Based Multi-Attention Model for X-Ray Imaging Report Generation

Xuwen Wang, Yu Zhang, Zhen Guo, Jiao Li
Pages: 21 - 32
The rapid growth of medical imaging data brings heavy pressure to radiologists for imaging diagnosis and report writing. This paper aims to extract valuable information automatically from medical images to assist doctors in chest X-ray image interpretation. Considering the different linguistic and visual...
Review Article

Application of Deep Learning in Microbiome

Qiang Zhu, Ban Huo, Han Sun, Bojing Li, Xingpeng Jiang
Pages: 23 - 29
With the rapid development of high-throughput sequencing technology, massive microbial data has been accumulated. The understanding of the microbial data could help us to find the relationships between microbes and diseases. However, due to the high dimensionality, sparseness, and complexity of the data,...
Research Article

Exploring the Microbiota-Gut-Brain Axis for Mental Disorders with Knowledge Graphs

Ting Liu, Xueli Pan, Xu Wang, K. Anton Feenstra, Jaap Heringa, Zhisheng Huang
Pages: 30 - 42
Gut microbiota has a significant influence on brain-related diseases through the communication routes of the gut-brain axis. Many species of gut microbiota produce a variety of neurotransmitters. In essence, the neurotransmitters are chemicals that influence mood, cognition, and behavior of the host....
Research Article

Deep High-Resolution Network for Low-Dose X-Ray CT Denoising

Ti Bai, Dan Nguyen, Biling Wang, Steve Jiang
Pages: 33 - 43
Low-dose computed tomography (LDCT) is clinically desirable because it reduces the radiation dose to patients. However, the quality of LDCT images is often suboptimal because of the inevitable strong quantum noise. Because of their unprecedented success in computer vision, deep learning (DL)-based techniques...
Research Article

Extraction of Characteristics of Time in “Tree Hole” Data

Xiaomin Jing, Shaofu Lin, Zhisheng Huang
Pages: 43 - 48
Statistics show that 15 percent of depressed people died by suicide, and more than 50 percent of depressed people are thinking about suicide. Worldwide, depression has become the second leading cause of death among people aged 15–29. This paper focus on the “tree hole” message data on microblog, and...
Research Article

Machine Learning for Violence Risk Assessment Using Dutch Clinical Notes

Pablo Mosteiro, Emil Rijcken, Kalliopi Zervanou, Uzay Kaymak, Floortje Scheepers, Marco Spruit
Pages: 44 - 54
Violence risk assessment in psychiatric institutions enables interventions to avoid violence incidents. Clinical notes written by practitioners and available in electronic health records are valuable resources capturing unique information, but are seldom used to their full potential. We explore conventional...
Research Article

Temporal Aspects of Tree Hole Data

Zengzhen Du, Dan Xie, Min Hu
Pages: 55 - 61
At present, adolescent suicide becomes a serious social problem. Many young people express suicidal thoughts through online social media. Weibo is a famous social media platform for real-time information sharing in China. When a Weibo user committed suicide, many other users continued to post information...
Research Article

Deep Learning–Based CT-to-CBCT Deformable Image Registration for Autosegmentation in Head and Neck Adaptive Radiation Therapy

Xiao Liang, Howard Morgan, Dan Nguyen, Steve Jiang
Pages: 62 - 75
The purpose of this study is to develop a deep learning–based method that can automatically generate segmentations on cone-beam computed tomography (CBCT) for head and neck online adaptive radiation therapy (ART), where expert-drawn contours in planning CT (pCT) images serve as prior knowledge. Because...
Research Article

Exploring Medical Students' and Faculty's Perception on Artificial Intelligence and Robotics. A Questionnaire Survey

Leandros Sassis, Pelagia Kefala-Karli, Marina Sassi, Constantinos Zervides
Pages: 76 - 84
Over the last decade, the emerging fields of artificial intelligence (AI) and robotics have been introduced in medicine, gaining much attention. This study aims to assess the insight of medical students and faculty regarding AI and robotics in medicine. A cross-sectional study was conducted among medical...
Research Article

Dosimetric Impact of Physician Style Variations in Contouring CTV for Postoperative Prostate Cancer: A Deep Learning–Based Simulation Study

Anjali Balagopal, Dan Nguyen, Maryam Mashayekhi, Howard Morgan, Aurelie Garant, Neil Desai, Raquibul Hannan, Mu-Han Lin, Steve Jiang
Pages: 85 - 96
Inter-observer variation is a significant problem in clinical target volume (CTV) segmentation in postoperative settings, where there is no gross tumor present. In this scenario, the CTV is not an anatomically established structure, but one determined by the physician based on the clinical guideline...

RadCloud—An Artificial Intelligence-Based Research Platform Integrating Machine Learning-Based Radiomics, Deep Learning, and Data Management

Geng Yayuan, Zhang Fengyan, Zhang Ran, Chen Ying, Xia Yuwei, Wang Fang, Yang Xunhong, Zuo Panli, Chai Xiangfei
Pages: 97 - 102
Radiomics and artificial intelligence (AI) are two rapidly advancing techniques in precision medicine for the purpose of disease diagnosis, prognosis, surveillance, and personalized therapy. This paper introduces RadCloud, an artificial intelligent (AI) research platform that supports clinical studies....