Journal of Artificial Intelligence for Medical Sciences

Volume 2, Issue 1-2, June 2021
Review Article

1. 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

2. 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

3. 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...
Research Article

4. 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

5. 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

6. 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

7. 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

8. 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

9. 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...

10. 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....