Search Results - "Vidya, Sudarshan"

Automated characterization and classification of coronary artery disease and myocardial infarction by decomposition of ECG signals: A comparative study by Acharya, U Rajendra, Fujita, Hamido, Adam, Muhammad, Lih, Oh Shu, Sudarshan, Vidya K, Hong, Tan Jen, Koh, Joel EW, Hagiwara, Yuki, Chua, Chua K., Poo, Chua Kok, San, Tan Ru

“…•Classification of three types of ECG beats are proposed.•Normal, CAD and MI are three classes considered in this work.•DCT, DWT and EMD decomposition methods…”
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Performance evaluation of Emergency Department patient arrivals forecasting models by including meteorological and calendar information: A comparative study by Sudarshan, Vidya K., Brabrand, Mikkel, Range, Troels Martin, Wiil, Uffe Kock

“…The volume of daily patient arrivals at Emergency Departments (EDs) is unpredictable and is a significant reason of ED crowding in hospitals worldwide. Timely…”
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A Novel Depression Diagnosis Index Using Nonlinear Features in EEG Signals by Acharya, U Rajendra, Sudarshan, Vidya K, Adeli, Hojjat, Santhosh, Jayasree, Koh, Joel E W, Puthankatti, Subha D, Adeli, Amir

“…Depression is a mental disorder characterized by persistent occurrences of lower mood states in the affected person. The electroencephalogram (EEG) signals are…”
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Automated characterization of coronary artery disease, myocardial infarction, and congestive heart failure using contourlet and shearlet transforms of electrocardiogram signal by Acharya, U Rajendra, Fujita, Hamido, Sudarshan, Vidya K, Oh, Shu Lih, Adam, Muhammad, Tan, Jen Hong, Koo, Jie Hui, Jain, Arihant, Lim, Choo Min, Chua, Kuang Chua

“…•Classification of normal, CAD, MI and CHF classes using ECG beat is proposed•CWT transform is performed on ECG beat•Contourlet and shearlet transforms are…”
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Computer-aided diagnosis of diabetic subjects by heart rate variability signals using discrete wavelet transform method by Rajendra Acharya, U., Vidya, K. Sudarshan, Ghista, Dhanjoo N., Lim, Wei Jie Eugene, Molinari, Filippo, Sankaranarayanan, Meena

“…•Automated identification of normal and diabetic subjects using HRV signals.•Features are extracted using DWT method.•Ranked features are subjected to various…”
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Computer-Aided Diagnosis of Depression Using EEG Signals by Acharya, U Rajendra, Sudarshan, Vidya K, Adeli, Hojjat, Santhosh, Jayasree, Koh, Joel E W, Adeli, Amir

“…The complex, nonlinear and non-stationary electroencephalogram (EEG) signals are very tedious to interpret visually and highly difficult to extract the…”
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Automated Characterization of Fatty Liver Disease and Cirrhosis Using Curvelet Transform and Entropy Features Extracted from Ultrasound Images by Acharya, U Rajendra, Raghavendra, U, Fujita, Hamido, Hagiwara, Yuki, Koh, Joel EW, Hong, Tan Jen, Sudarshan, Vidya K, Vijayananthan, Anushya, Yeong, Chai Hong, Gudigar, Anjan, Ng, Kwan Hoong

“…Abstract Fatty liver disease (FLD) is reversible disease and can be treated, if it is identified at an early stage. However, if diagnosed at the later stage,…”
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Towards precision medicine: from quantitative imaging to radiomics by Acharya, U. Rajendra, Hagiwara, Yuki, Sudarshan, Vidya K., Chan, Wai Yee, Ng, Kwan Hoong

“…Radiology (imaging) and imaging-guided interventions, which provide multi-parametric morphologic and functional information, are playing an increasingly…”
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Computer-aided diagnosis of Myocardial Infarction using ultrasound images with DWT, GLCM and HOS methods: A comparative study by Vidya, K. Sudarshan, Ng, E.Y.K, Acharya, U. Rajendra, Chou, Siaw Meng, Tan, Ru San, Ghista, Dhanjoo N

“…Abstract Myocardial Infarction (MI) or acute MI (AMI) is one of the leading causes of death worldwide. Precise and timely identification of MI and extent of…”
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Longitudinal Changes in Tear Evaporation Rates After Eyelid Warming Therapies in Meibomian Gland Dysfunction by Yeo, Sharon, Tan, Jen Hong, Acharya, U Rajendra, Sudarshan, Vidya K, Tong, Louis

“…Lid warming is the major treatment for meibomian gland dysfunction (MGD). The purpose of the study was to determine the longitudinal changes of tear…”
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Automated characterization of cardiovascular diseases using relative wavelet nonlinear features extracted from ECG signals by Adam, Muhammad, Oh, Shu Lih, Sudarshan, Vidya K, Koh, Joel EW, Hagiwara, Yuki, Tan, Jen Hong, Tan, Ru San, Acharya, U Rajendra

“…•Classification of normal, DCM, HCM and MI ECG signals.•Four seconds of ECG segments are used.•Nonlinear features are extracted from DWT decomposition.•Feature…”
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Application of wavelet techniques for cancer diagnosis using ultrasound images: A Review by Sudarshan, Vidya K, Mookiah, Muthu Rama Krishnan, Acharya, U Rajendra, Chandran, Vinod, Molinari, Filippo, Fujita, Hamido, Ng, Kwan Hoong

“…Abstract Ultrasound is an important and low cost imaging modality used to study the internal organs of human body and blood flow through blood vessels. It uses…”
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Future IoT tools for COVID‐19 contact tracing and prediction: A review of the state‐of‐the‐science by Jahmunah, Vicnesh, Sudarshan, Vidya K., Oh, Shu Lih, Gururajan, Raj, Gururajan, Rashmi, Zhou, Xujuan, Tao, Xiaohui, Faust, Oliver, Ciaccio, Edward J., Ng, Kwan Hoong, Acharya, U. Rajendra

“…In 2020 the world is facing unprecedented challenges due to COVID‐19. To address these challenges, many digital tools are being explored and developed to…”
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Automated Detection of Premature Delivery Using Empirical Mode and Wavelet Packet Decomposition Techniques with Uterine Electromyogram Signals by Acharya, U Rajendra, Sudarshan, Vidya K, Rong, Soon Qing, Tan, Zechariah, Min, Lim Choo, Koh, Joel EW, Nayak, Sujatha, Bhandary, Sulatha V

“…Abstract An accurate detection of preterm labor and the risk of preterm delivery before 37 weeks of gestational age is crucial to increase the chance of…”
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Functional interactions between complex I and complex II with nNOS in regulating cardiac mitochondrial activity in sham and hypertensive rat hearts by Wu, Yu Na, Sudarshan, Vidya K, Zhu, Shi Chao, Shao, Yong Feng, Kim, Sung Joon, Zhang, Yin Hua

“…Nitric oxide (NO) affects mitochondrial activity through its interactions with complexes. Here, we investigated regulations of complex I (C-I) and complex II…”
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Retraction Note: Application of empirical mode decomposition (EMD) for automated identification of congestive heart failure using heart rate signals by Acharya, U. Rajendra, Fujita, Hamido, Sudarshan, Vidya K., Oh, Shu Lih, Muhammad, Adam, Koh, Joel E. W., Tan, Jen Hong, Chua, Chua K., Chua, Kok Poo, Tan, Ru San

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Ultrasound-based tissue characterization and classification of fatty liver disease: A screening and diagnostic paradigm by Acharya, U. Rajendra, Faust, Oliver, Molinari, Filippo, Sree, S. Vinitha, Junnarkar, Sameer P., Sudarshan, Vidya

“…•We review the modalities that detect Fatty Liver Disease (FLD).•We review the ultrasound-based Computer Aided Diagnostic techniques for FLD detection.•We…”
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Application of entropies for automated diagnosis of epilepsy using EEG signals: A review by Acharya, U. Rajendra, Fujita, H., Sudarshan, Vidya K., Bhat, Shreya, Koh, Joel E.W.

“…•Epilepsy can be detected using EEG signals.•The entropy indicates the complexity of the EEG signal.•Various entropies are used to diagnose epilepsy.•Unique…”
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Automated interpretation of biopsy images for the detection of celiac disease using a machine learning approach by Koh, Joel En Wei, De Michele, Simona, Sudarshan, Vidya K, Jahmunah, V, Ciaccio, Edward J., Ooi, Chui Ping, Gururajan, Raj, Gururajan, Rashmi, Oh, Shu Lih, Lewis, Suzanne K., Green, Peter H., Bhagat, Govind, Acharya, U Rajendra

“…•First machine learning technique for automated detection and classification of celiac disease using biopsy images.•Steerable Pyramid Transform and nonlinear…”
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Application of empirical mode decomposition (EMD) for automated identification of congestive heart failure using heart rate signals by Acharya, U Rajendra, Fujita, Hamido, Sudarshan, Vidya K, Oh, Shu Lih, Muhammad, Adam, Koh, Joel E W, Jen Hong Tan, Chua, Chua K, Kok Poo Chua, Ru San Tan

“…Electrocardiogram is widely used to diagnose the congestive heart failure (CHF). It is the primary noninvasive diagnostic tool that can guide in the management…”
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