Search Results - "Pastika, Libor"

Artificial intelligence-enhanced electrocardiography derived body mass index as a predictor of future cardiometabolic disease by Pastika, Libor, Sau, Arunashis, Patlatzoglou, Konstantinos, Sieliwonczyk, Ewa, Ribeiro, Antônio H., McGurk, Kathryn A., Khan, Sadia, Mandic, Danilo, Scott, William R., Ware, James S., Peters, Nicholas S., Ribeiro, Antonio Luiz P., Kramer, Daniel B., Waks, Jonathan W., Ng, Fu Siong

“…The electrocardiogram (ECG) can capture obesity-related cardiac changes. Artificial intelligence-enhanced ECG (AI-ECG) can identify subclinical disease. We…”
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Abstract 4137169: Artificial Intelligence-Enabled Electrocardiography For The Prediction of Future Type 2 Diabetes Mellitus by Pastika, Libor, Patlatzoglou, Konstantinos, Sieliwonczyk, Ewa, Barker, Joseph, Zeidaabadi, Boroumand, McGurk, Kathryn, Khan, Sadia, Mandic, Danilo, Ware, James, Peters, Nicholas, Kramer, Daniel, Waks, Jonathan, Sau, Arunashis, Ng, Fu Siong

“…Abstract only Background: Undiagnosed diabetes and prediabetes present a significant global health challenge. Artificial Intelligence-enabled…”
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PO-03-008 ARTIFICIAL INTELLIGENCE-ENHANCED ELECTROCARDIOGRAPHY IDENTIFIES FEMALE-SPECIFIC ELEVATED CARDIOVASCULAR RISK PROFILE by Sau, Arunashis, Sieliwonczyk, Ewa, Patlatzoglou, Konstantinos, Pastika, Libor, McGurk, Kathryn, Ribeiro, Antônio, Ribeiro, Antonio L., Peters, Nicholas S., Ware, James S., Tayal, Upasana, Kramer, Daniel B., Waks, Jonathan, Ng, Fu Siong

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Abstract 13245: Neural Network-Derived Electrocardiographic Features Predict Future Cardiovascular Disease and All-Cause Mortality by Sau, Arunashis, Ribeiro, Antonio, McGurk, Kathryn A, Pastika, Libor, Bajaj, Nikesh, Ardissino, Maddalena, Chen, Jun Yu, Wu, Huiyi, Shi, Xili, Hnatkova, Katerina, Zheng, Sean, Britton, Anne, Shipley, Martin J, Andršová, Irena, Novotny, Tomas, Sabino, Ester Cerdeira, Giatti, Luana, Barreto, Sandhi Maria, Waks, Jonathan W, Kramer, Daniel B, Mandic, Danilo, Peters, Nicholas S, O'Regan, Declan, Malik, Marek, Ware, James S, Ribeiro, Antonio, Ng, Fu Siong

“…Abstract only Background Subtle prognostically-important ECG features may not be apparent to physicians. In the course of supervised machine learning (ML),…”
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CE-469620-001 AN ARTIFICIAL INTELLIGENCE–ENABLED ELECTROCARDIOGRAPHY PLATFORM FOR MORTALITY, ATHEROSCLEROTIC CARDIOVASCULAR DISEASE, HEART FAILURE AND VENTRICULAR ARRHYTHMIA PREDICTION by Sau, Arunashis, Pastika, Libor, Sieliwonczyk, Ewa, Patlatzoglou, Konstantinos, Ribeiro, Antonio, McGurk, Kathryn, Zeidaabadi, Boroumand, Zhang, Henry, Macierzanka, Krzysztof, Mandic, Danilo, Sabino, Ester, Giatti, Luana, Barreto, Sandhi, Camelo, Lidyane d., Tzoulaki, Ioanna, O'Regan, Declan P., Peters, Nicholas S., Ware, James S., Ribeiro, Antonio L., Kramer, Daniel B., Waks, Jonathan, Ng, Fu Siong

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Prognostic Significance and Associations of Neural Network–Derived Electrocardiographic Features by Sau, Arunashis, Ribeiro, Antônio H., McGurk, Kathryn A., Pastika, Libor, Bajaj, Nikesh, Gurnani, Mehak, Sieliwonczyk, Ewa, Patlatzoglou, Konstantinos, Ardissino, Maddalena, Chen, Jun Yu, Wu, Huiyi, Shi, Xili, Hnatkova, Katerina, Zheng, Sean L., Britton, Annie, Shipley, Martin, Andršová, Irena, Novotný, Tomáš, Sabino, Ester C., Giatti, Luana, Barreto, Sandhi M., Waks, Jonathan W., Kramer, Daniel B., Mandic, Danilo, Peters, Nicholas S., O’Regan, Declan P., Malik, Marek, Ware, James S., Ribeiro, Antonio Luiz P., Ng, Fu Siong

“…BACKGROUND: Subtle, prognostically important ECG features may not be apparent to physicians. In the course of supervised machine learning, thousands of ECG…”
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A comparison of artificial intelligence-enhanced electrocardiography approaches for prediction of time-to-mortality using electrocardiogram images by Sau, Arunashis, Zeidaabadi, Boroumand, Patlatzoglou, Konstantinos, Pastika, Libor, Ribeiro, Antônio H, Sabino, Ester, Peters, Nicholas S, Ribeiro, Antonio Luiz P, Kramer, Daniel B, Waks, Jonathan W, Ng, Fu Siong

“…Abstract Background Most artificial intelligence-enhanced ECG (AI-ECG) models used to predict adverse events including death require that the ECGs be stored…”
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Machine learning-derived cycle length variability metrics predict spontaneously terminating ventricular tachycardia in implantable cardioverter defibrillator recipients by Sau, Arunashis, Ahmed, Amar, Chen, Jun Yu, Pastika, Libor, Wright, Ian, Li, Xinyang, Handa, Balvinder, Qureshi, Norman, Koa-Wing, Michael, Keene, Daniel, Malcolme-Lawes, Louisa, Varnava, Amanda, Linton, Nicholas W F, Lim, Phang Boon, Lefroy, David, Kanagaratnam, Prapa, Peters, Nicholas S, Whinnett, Zachary, Ng, Fu Siong

“…Implantable cardioverter defibrillator (ICD) therapies have been associated with increased mortality and should be minimized when safe to do so. We…”
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MP-470543-005 UNSUPERVISED ECG FEATURE EXTRACTION USING DEEP LEARNING EMPOWERS DISCOVERY OF GENETIC DETERMINANTS OF CARDIAC ELECTROPHYSIOLOGY by Sieliwonczyk, Ewa, Sau, Arunashis, Patlatzoglou, Konstantinos, McGurk, Kathryn, Pastika, Libor, Thami, Prisca, Mangino, Massimo, Zheng, Sean, Powell, George, Curran, Lara, Buchan, Rachel, Theotokis, Pantazis, Peters, Nicholas S., Loeys, Bart, Kramer, Daniel B., Waks, Jonathan, Ng, Fu Siong, Ware, James S.

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Artificial intelligence-enabled electrocardiogram for mortality and cardiovascular risk estimation: a model development and validation study by Sau, Arunashis, Pastika, Libor, Sieliwonczyk, Ewa, Patlatzoglou, Konstantinos, Ribeiro, Antônio H, McGurk, Kathryn A, Zeidaabadi, Boroumand, Zhang, Henry, Macierzanka, Krzysztof, Mandic, Danilo, Sabino, Ester, Giatti, Luana, Barreto, Sandhi M, Camelo, Lidyane do Valle, Tzoulaki, Ioanna, O'Regan, Declan P, Peters, Nicholas S, Ware, James S, Ribeiro, Antonio Luiz P, Kramer, Daniel B, Waks, Jonathan W, Ng, Fu Siong

“…Artificial intelligence (AI)-enabled electrocardiography (ECG) can be used to predict risk of future disease and mortality but has not yet been adopted into…”
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DH-452784-1 UNSUPERVISED MACHINE LEARNING IDENTIFIES PROGNOSTICALLY SIGNIFICANT PHENOGROUPS FROM NEURAL NETWORK-DERIVED ECG FEATURES by Sau, Arunashis, Ribeiro, Antônio H., McGurk, Kathryn, Pastika, Libor, Bajaj, Nikesh, Chen, Jun Yu, Wu, Huiyi, Shi, Xili, Hnatkova, Katerina, Zheng, Sean, Briton, Annie, Shipley, Martin, Andršová, Irena, Novotný, Tomáš, Sabino, Ester, Waks, Jonathan W., Kramer, Daniel B., Mandic, Danilo, Peters, Nicholas S., Malik, Marek, Ware, James S., Ribeiro, Antonio L., Ng, Fu Siong

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