Comparison of resting and adenosine-free pressure indices with adenosine-induced hyperemic fractional flow reserve in intermediate coronary lesions

Autor: Deep Chandh Raja, Vijayakumar Subban, Rony Mathew, Jabir Abdullakutty, Jo Joseph, Jimmy George, Subash Chandra, Nandhini Livingston, Shyam G. Nair, Ezhilan Janakiraman, Latchumanadhas Kalidoss, Ajit Sankaradas Mullasari

Publikováno v: Indian Heart Journal, Vol 71, Iss 1, Pp 74-79 (2019)

Objective: Fractional flow reserve (FFR) using adenosine has been the gold standard in the functional assessment of intermediate coronary stenoses in the catheterization laboratory. We aim to study the correlation of adenosine-free indices such as wh

Externí odkaz: https://doaj.org/article/3d7929042cf844c5a708c77156785254

A clinico-epidemiological study of dermatoses in pediatric HIV patients in a tertiary care center

Autor: Sukumaran Pradeep Nair, Rony Mathew

Publikováno v: Indian Journal of Paediatric Dermatology, Vol 17, Iss 3, Pp 186-189 (2016)

Introduction: Cutaneous lesions are very common in pediatric HIV infection, and many of the dermatoses are linked to the underlying levels of CD4 counts. Aims: The primary aim was to study the clinico-epidemiological patterns of dermatoses in pediatr

Externí odkaz: https://doaj.org/article/f95bef3cb4874487899d42d26cfa123d

A Novel Deep Learning Approach for Forecasting Myocardial Infarction Occurrences with Time Series Patient Data.

Autor: Sayed MS; Department of Statistics, Jahangirnagar University, Dhaka, Bangladesh., Rony MAT; Department of Statistics, Noakhali Science & Technology University, Noakhali, 3814, Bangladesh., Islam MS; Department of Computer Science and Telecommunication Engineering, Noakhali Science & Technology University, Noakhali, 3814, Bangladesh., Raza A; Department of Software Engineering, University Of Lahore, Lahore, 54000 , Pakistan. ali.raza.scholarly@gmail.com., Tabassum S; Department of Statistics, Noakhali Science & Technology University, Noakhali, 3814, Bangladesh., Daoud MS; College of Engineering, Al Ain University, Abu Dhabi, 112612, UAE., Migdady H; CSMIS Department, Oman College of Management and Technology, Barka, 320, Oman., Abualigah L; Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, 19328, Jordan. aligah@usm.my.; Computer Science Department, Al al-Bayt University, Mafraq, 25113, Jordan. aligah@usm.my.; MEU Research Unit, Middle East University, Amman, 11831, Jordan. aligah@usm.my.; Applied science research center, Applied science private university, Amman, 11931, Jordan. aligah@usm.my.; Artificial Intelligence and Sensing Technologies (AIST) Research Center, University of Tabuk, Tabuk, 71491, Saudi Arabia. aligah@usm.my.

Publikováno v: Journal of medical systems [J Med Syst] 2024 May 22; Vol. 48 (1), pp. 53. Date of Electronic Publication: 2024 May 22.

ML-CKDP: Machine learning-based chronic kidney disease prediction with smart web application.

Autor: Halder RK; Dept. of Computer Science and Engineering, Jagannath University, Dhaka 1100, Bangladesh., Uddin MN; Dept. of Computer Science and Engineering, Jagannath University, Dhaka 1100, Bangladesh., Uddin MA; School of Information Technology, Deakin University, Geelong 3125, Australia., Aryal S; School of Information Technology, Deakin University, Geelong 3125, Australia., Saha S; Dept. of Computer Science and Engineering, Jagannath University, Dhaka 1100, Bangladesh., Hossen R; Dept. of Cyber Security, Bangabandhu Sheikh Mujibur Rahman Digital University, Kaliakoir, Gazipur 1750, Bangladesh., Ahmed S; Dept. of Educational Technology, Bangabandhu Sheikh Mujibur Rahman Digital University, Kaliakoir, Gazipur 1750, Bangladesh., Rony MAT; Dept. of Statistics, Noakhali Science and Technology University, Noakhali 3814, Bangladesh., Akter MF; Dept. of Computer Science and Engineering, Jagannath University, Dhaka 1100, Bangladesh.

Publikováno v: Journal of pathology informatics [J Pathol Inform] 2024 Feb 22; Vol. 15, pp. 100371. Date of Electronic Publication: 2024 Feb 22 (Print Publication: 2024).

Fanconi Anemia: Examining Guidelines for Testing All Patients with Hand Anomalies Using a Machine Learning Approach.

Autor: Wallner C; Department of Plastic Surgery, Great Ormond Street Hospital, London WC1N 3JH, UK.; Department of Plastic and Hand Surgery, Burn Center Sarcoma Center, BG University Hospital Bergmannsheil Bochum, Ruhr University Bochum, 44789 Bochum, Germany., Hurst J; Department of Plastic Surgery, Great Ormond Street Hospital, London WC1N 3JH, UK., Behr B; Department of Plastic and Hand Surgery, Burn Center Sarcoma Center, BG University Hospital Bergmannsheil Bochum, Ruhr University Bochum, 44789 Bochum, Germany., Rony MAT; Department of Statistics, Noakhali Science and Technology University, Noakhali 3814, Bangladesh., Barabás A; Department of Plastic Surgery, Great Ormond Street Hospital, London WC1N 3JH, UK., Smith G; Department of Plastic Surgery, Great Ormond Street Hospital, London WC1N 3JH, UK.

Publikováno v: Children (Basel, Switzerland) [Children (Basel)] 2022 Jan 07; Vol. 9 (1). Date of Electronic Publication: 2022 Jan 07.