Interdisciplinary Research in Iran VII: The Convergence of Biology and Artificial Intelligence [0.03%]
伊朗的跨学科研究第七期：生物学与人工智能的融合
Alireza Ani,Ahmad Vaez
Alireza Ani
Zoha Kamali,Amir Jalilvandnejad,Bentolhoda Falenji et al.
Zoha Kamali et al.
Background: Systems biology is an interdisciplinary approach, which will fundamentally transform the way biology is perceived and studied. Subsequently, biomedical knowledge, medical practice, health systems, and related ...
Human Stress Classification Using Cardiovascular and Respiratory Data Based on Machine Learning Techniques [0.03%]
基于机器学习技术的心血管和呼吸数据的人体压力分类方法
Mahdis Yaghoubi,Navid Adib,Abolfazl Rezaei Monfared et al.
Mahdis Yaghoubi et al.
Background: Stress, a widespread mental health concern, significantly impacts people well-being and performance. This study proposes a novel approach to stress detection by fusing cardiovascular and respiratory data. ...
Artificial Intelligence-based Automated International Classification of Diseases Coding: A Systematic Review [0.03%]
基于人工智能的自动疾病国际分类编码：系统性综述
Seyyedeh Fatemeh Mousavi Baigi,Masoumeh Sarbaz,Ali Darroudi et al.
Seyyedeh Fatemeh Mousavi Baigi et al.
Automated clinical coding, facilitated by artificial intelligence (AI) techniques like natural language processing and machine learning, has emerged as a promising approach to enhance coding efficiency and accuracy in healthcare. This revie...
A New Method for Dynamic Brain Connectivity Analysis Based on Tensor Decomposition in Tinnitus Using High-density Electroencephalogram in Source Domain [0.03%]
基于张量分解的耳鸣高密度脑电源网络动态连接性分析新方法研究
Moein Bahman,Seyed Saman Sajadi,Iman Ghodrati Toostani et al.
Moein Bahman et al.
Background: Functional connectivity (FC), defined as the statistical reliance among different brain regions, has been an effective tool for studying cognitive brain functions. The majority of existing FC-based research ha...
Designing a Software for Registry of Pregnant Women with Heart Disease in Iran and Preliminary Results [0.03%]
伊朗妊娠期心脏病女性登记软件的设计及初步结果
Mahdi Kalani,Fateme Mahdikhoshouei,Parvin Bahrami et al.
Mahdi Kalani et al.
Heart disease in pregnancy is an important health issue worldwide which needs precise care to improve pregnant women health care and reduce maternal mortality rate (MMR). As we know registries play an important role in improvement of health...
A Nonlinear Method to Identify Seizure Dynamic Trajectory Based on Variance of Recurrence Rate in Human Epilepsy Patients Using EEG [0.03%]
基于EEG的复发率变异性的一种非线性方法鉴别癫痫患者的动态轨迹
Morteza Farahi,Seyed Saman Sajadi,Fateme Karbasi et al.
Morteza Farahi et al.
Background: Surgery is a well-established treatment for drug-resistant epilepsy, but outcomes are often suboptimal, especially when no lesion is visible on preoperative imaging. A major challenge in determining the seizur...
Balancing Radiation Dose Reduction and Image Quality in Chest Computed Tomography using Silicon Rubber-barium Sulfate Composite Shield [0.03%]
硅橡胶-硫酸钡复合材料在胸部CT检查中的应用：剂量体积与图像质量的权衡研究
Mohammad Keshtkar,Saeedeh Yazdanifar
Mohammad Keshtkar
Background: During chest CT examinations, the breasts are exposed to a significant amount of radiation, increasing the risk of radiation-induced cancers. The objective of this study is to develop and evaluate a novel sili...
A Comprehensive Survey of Brain-Computer Interface Technology in Health care: Research Perspectives [0.03%]
脑机接口技术在医疗健康领域的研究进展与展望综述式评论文章
Meenalosini Vimal Cruz,Suhaima Jamal,Sibi Chakkaravarthy Sethuraman
Meenalosini Vimal Cruz
The brain-computer interface (BCI) technology has emerged as a groundbreaking innovation with profound implications across diverse domains, particularly in health care. By establishing a direct communication pathway between the human brain ...
Introducing a Deep Neural Network Model with Practical Implementation for Polyp Detection in Colonoscopy Videos [0.03%]
一种实用的结肠内镜中息肉检测深度神经网络模型及其应用研究
Hajar Keshavarz,Zohreh Ansari,Hossein Abootalebian et al.
Hajar Keshavarz et al.
Background: Deep learning has gained much attention in computer-assisted minimally invasive surgery in recent years. The application of deep-learning algorithms in colonoscopy can be divided into four main categories: sur...