A
Ahmad Khairuddin Mohamed Yusof
Researcher at National Institutes of Health
Publications - 11
Citations - 56
Ahmad Khairuddin Mohamed Yusof is an academic researcher from National Institutes of Health. The author has contributed to research in topics: Medicine & Internal medicine. The author has an hindex of 2, co-authored 7 publications receiving 11 citations.
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Journal ArticleDOI
Systematic Scoring Balloon Lesion Preparation for Drug-Coated Balloon Angioplasty in Clinical Routine: Results of the PASSWORD Observational Study.
Klaus Bonaventura,Markus Schwefer,Ahmad Khairuddin Mohamed Yusof,Matthias Waliszewski,Matthias Waliszewski,Florian Krackhardt,Philip Steen,Raymundo Ocaranza,Ahmad Syadi Mahmood Zuhdi,Liew Houng Bang,Kristof Graf,Ulrich Böck,Kenneth Chin +12 more
TL;DR: The routine use of a non-slip element scoring balloon catheter to prepare lesions suitable for drug-coated balloon angioplasty is associated with high procedural success rates and low TLF rates in de novo lesions.
Journal ArticleDOI
Apixaban versus Warfarin in Patients with Left Ventricular Thrombus: A Pilot Prospective Randomized Outcome Blinded Study Investigating Size Reduction or Resolution of Left Ventricular Thrombus
W. Yus Haniff W. Isa,Niny Hwong,Ahmad Khairuddin Mohamed Yusof,Zurkurnai Yusof,Ng Seng Loong,Nadiah Wan-Arfah,Nyi Nyi Naing +6 more
TL;DR: In this article, the authors investigated the size reduction or resolution of left ventricular thrombus with apixaban compared to conventional warfarin compared to VKA oral anticoagulants.
Journal ArticleDOI
Real-time Detection of Aortic Valve in Echocardiography using Convolutional Neural Networks.
Muhammad Hanif Ahmad Nizar,Chow Khuen Chan,Azira Khalil,Ahmad Khairuddin Mohamed Yusof,Khin Wee Lai +4 more
TL;DR: The findings provide a foundation for implementing a convolutional detection system to echocardiography for medical purposes and can provide further medical analysis from the resulting detection.
Proceedings ArticleDOI
Detection of Aortic Valve from Echocardiography in Real-Time Using Convolutional Neural Network
Muhammad Hanif Ahmad Nizar,Chow Khuen Chan,Ahmad Khairuddin Mohamed Yusof,Azira Khalil,Khin Wee Lai +4 more
TL;DR: The findings in this study facilitate a foundation in utilizing convolutional neural network to the echocardiography field and show that the Faster R-CNN Inception v2 attained the best accuracy and F1 score.
Journal ArticleDOI
Automated Classification of Atherosclerotic Radiomics Features in Coronary Computed Tomography Angiography (CCTA)
Mardhiyati Mohd Yunus,Ahmad Khairuddin Mohamed Yusof,Muhd Zaidi Ab Rahman,Xue Jing Koh,Akmal Sabarudin,Puteri N. E. Nohuddin,Kwan Hoong Ng,Mohd Mustafa Awang Kechik,Muhammad Khalis Abdul Karim +8 more
TL;DR: Overall, TPOT shown promising capabilities in terms of finding the best pipeline and tailoring the model using CCTA-based radiomic datasets, which are a key point for prediction of cardiac events.