Machine-Learning Insights from the Framingham Heart Study: Enhancing Cardiovascular Risk Prediction and Monitoring by Emi Yuda, Itaru Kaneko, Daisuke Hirahara

Get full text

A short report on the current landscape of Artificial Intelligence (AI) in vascular surgery in Pakistan by Nadeem Ahmed Siddiqui, Muhammad Anees, Fareed Shaikh, Zia Ur Rehman

“…It can enhance healthcare accessibility, improve diagnostic accuracy, and alleviate the workload on vascular surgeons. …”
Get full text

A comprehensive review of deepfakes in medical imaging: Ethical concerns, detection techniques and future directions by Pradepan P, Gladston Raj S, Juby George K

“…These deep fakes appear very similar to real diagnostic scans and are often difficult to distinguish from real medical images. …”
Get full text

Precision Agriculture: Utilizing Machine Learning for Accurate Plant Disease Diagnosis by Divya Banti, Tandan Gajendra

“…While ML has been applied to the precise diagnosis of plant diseases in this research, it was found to have a great potential to improve agricultural outcomes. …”
Get full text

Results of a non-interventional multicenter observational study on the diagnosis and treatment of patients with axial psoriatic arthritis in rea-world clinical practice in the Russ... by T. V. Korotaeva, E. E. Gubar, E. Yu. Loginova, Yu. L. Korsakova, E. A. Vasilenko, I.-D. Yu. Ilyevsky, L. V. Ivanova, E. Yu. Akulinushkina, P. А. Shesternya, O. V. Matveychuk, Yu. Yu. Grabovetskaya, A. A. Barakat, M. A. Korolev, E. V. Zonova, O. A. Georginova, I. V. Kolotilina, I. M. Marusenko, I. B. Vinogradova, O. B. Nesmeyanova, N. E. Grigoriadi, A. V. Petrov, D. G. Krechikova, T. V. Kropotina, S. P. Yakupova, V. I. Mazurov

Get full text

Evolution of AI enabled healthcare systems using textual data with a pretrained BERT deep learning model by Yi Jie Wang, Wei Chong Choo, Keng Yap Ng, Ran Bi, Peng Wei Wang

“…This study not only reveals current research hotspots and technological trends in AI for healthcare but also proposes an advanced research method. …”
Get full text

Spatial vector cardiography: From origins to the present day. A review by Valentin E. Oleynikov, Angelina A. Chernova

“…Despite the fact that the idea of constructing an electric vector of the heart quickly gained appreciation among scientists of that time, the technical imperfections of electrocardiographs and the complexity of manual calculations for a certain period of time reduced the interest of researchers in this method. The advent of digital electrocardiographs and the development of algorithms for the automatic construction of heart vectors gave VCG a second life and allowed us to look at vector theory from a different angle. …”
Get full text

Chronic liver disease detection using ranking and projection-based feature optimization with deep learning by Sumaiya Noor, Salman A. AlQahtani, Salman Khan

“…Additionally, the rise of deep learning has begun transforming liver research, offering powerful tools to aid doctors in diagnosis and treatment. …”
Get full text

Development and validation of machine learning models predicting hospitalizations of hypertensive patients over 12 months by A. E. Andreychenko, A. D. Ermak, D. V. Gavrilov, R. E. Novitsky, O. M. Drapkina, A. V. Gusev

Get full text

Novel CYCLIN‐O pathogenic variants in a patient presenting with bronchiectasis secondary to reduced generation of multiple motile cilia by Kim Hoong Yap, Albert Yick Hou Lim, Biju Thomas, Carine Bonnard, Emmanuelle Szenker‐Ravi, Yan Ling Chong, Sudipto Roy, Bruno Reversade

Get full text

Enhancement in dynamic range for dual-rotating retarder Mueller matrix polarimetry by Jiongying Lv, Shuan Yao, Nan Zeng, Caizhong Guan, Honghui He

“…Mueller matrix polarimetry (MMP) has been proven to be a powerful tool for characterizing the microstructural features of biological samples in biomedical research and clinical diagnostics. However, the traditional Mueller matrix (MM) imaging technique based on single exposure has a limited dynamic range, leading to poor polarization image quality for biological samples with significant contrast variations. …”
Get full text

Integrated machine learning and bioinformatic analysis of mitochondrial-related signature in chronic rhinosinusitis with nasal polyps by Bo Yang, MMed, Min Gu, MMed, Chen Hong, MMed, Xin-Yuan Zou, MMed, Jia-Qi Zhang, MBBS, Ye Yuan, MBBS, Chang-Yu Qiu, MD, MSc, Mei-Ping Lu, MD, PhD, Lei Cheng, MD, PhD

Get full text

EPIGENETIC REGULATION OF GENE EXPRESSION IN HEAD AND NECK SQUAMOUS CELL CARCINOMA: THERAPEUTIC PERSPECTIVES by R. B. Samsonov, Z. A. Radzhabova, Yu. V. Cheburkin, V. A. Klyuge, E. V. Tkachenko, A. V. Malek

Get full text

Predicting mother and newborn skin-to-skin contact using a machine learning approach by Sanaz Safarzadeh, Nastaran Safavi Ardabili, Mohammadsadegh Vahidi Farashah, Nasibeh Roozbeh, Fatemeh Darsareh

“…Doula support, neonatal weight, gestational age, attending childbirth classes, and maternal age were the critical predictors for SSC based on the top two algorithms with superior performance. Conclusions Although this study found that the ML model performed well in predicting SSC, more research is needed to make a better conclusion about its performance.…”
Get full text

Analysis of the Results of a Questionnaire Survey of Doctors and Clinical Psychologists on Somatovegetative Symptoms of Stress by Anna A. Kuzyukova, Natalia A. Levchenko, Larisa A. Marchenkova

“…Modern digital technologies make it possible to create algorithms that include a large amount of clarifying data, and, at the same time, select only the information necessary for a particular case during diagnostics, saving time. …”
Get full text

Artificial intelligence for chest X-ray image enhancement by Liming Song, Hongfei Sun, Haonan Xiao, Sai Kit Lam, Yuefu Zhan, Ge Ren, Jing Cai

“…Recently, the successful application of deep learning (DL) algorithms in medical image analysis has prompted researchers to propose and design DL-based CXR image enhancement algorithms. …”
Get full text

Using New Technologies to Analyze Gut Microbiota and Predict Cancer Risk by Mohammad Amin Hemmati, Marzieh Monemi, Shima Asli, Sina Mohammadi, Behina Foroozanmehr, Dariush Haghmorad, Valentyn Oksenych, Majid Eslami

“…Early detection is made easier by machine learning algorithms that improve the categorization of cancer kinds based on microbiological data. …”
Get full text

Demographic and clinical features of nontuberculous mycobacteria infection resulting from cosmetic procedures: a systematic review by Xiao Ma, Xing-Yu Li, Jia-Wei Liu

“…Further research is needed to standardize management algorithms.…”
Get full text

SIMULTANEOUS PANCREAS-KIDNEY TRANSPLANTATION: EARLY POSTOPERATIVE COMPLICATIONS by M.Sh. Khubutia, A.V Pinchuk, I.V. Dmitriev, K.E. Lazareva, A.G. Balkarov, R.V. Storozhev, N.V. Shmarina

Get full text

Development and validation of a prognostic staging system for primary plasma cell leukemia by Mengru Tian, Gang An, Weijun Fu, Wenqiang Yan, Lu Li, Chunyan Sun, Zhenyu Li, Lijuan Chen, Aijun Liao, Guangxun Gao, Xiaoqi Qin, Mengyao Li, Chunrui Li, Hua Xue, Li Gao, Yi Wang, Aili He, Fan Zhou, Dongmei Guo, Yujun Dong, Zhihong Fang, Xiaoxia Chu, Jianqing Mi, Chengcheng Fu, Hui Zeng, Shuling Hou, Xiaotao Wang, Hua Wang, Yongqiang Wei, Xinyue Liang, Xingcheng Yi, Yue Sun, Lugui Qiu, Yun Dai, Fengyan Jin

Get full text