Results 81 to 90 of about 421,250 (298)

Multimodal Wearable Biosensing Meets Multidomain AI: A Pathway to Decentralized Healthcare

Advanced Science, EarlyView.
Multimodal biosensing meets multidomain AI. Wearable biosensors capture complementary biochemical and physiological signals, while cross‐device, population‐aware learning aligns noisy, heterogeneous streams. This Review distills key sensing modalities, fusion and calibration strategies, and privacy‐preserving deployment pathways that transform ...
Chenshu Liu, Haolin Fan, Minwoo Kim, Tong Zhou, Pinyi Yang, Lingdi Zhao, Yiran Wang, Ziyuan Che, Chia‐Wei Liu, Bingbing Li, Yangzhi Zhu   +10 more
wiley   +1 more source

External Validation of Cardiovascular Risk Scores in the Southern Cone of Latin America: Which Predicts Better? [PDF]

, 2018
Introducción: La estimación inexacta del riesgo cardiovascular poblacional puede llevar a un manejo inadecuado de las intervenciones médicas preventivas, como, por ejemplo, el uso de estatinas.
Danaei, Goodarz, Gulayin, Pablo Elías, Gutierrez, Laura, Irazola, Vilma, Lanas, Fernando, Poggio, Rosana, Ponzo, Jaqueline, Rubinstein, Adolfo Luis   +7 more
core  

Elevated Risk of Complications in Patients Receiving Dual Antithrombotic Therapy Undergoing Hepatectomy: A Single‐Center Audit of 749 Cases

Annals of Gastroenterological Surgery, EarlyView.
This single‐center retrospective study evaluated perioperative outcomes after hepatectomy in 749 patients, including 140 receiving ATT, using propensity score matching to compare ATT and non‐ATT cohorts. Under standardized perioperative management, ATT did not increase major bleeding, transfusion, or severe morbidity overall; however, within the ATT ...
Haruki Mori, Hiromitsu Maehira, Nobuhito Nitta, Takeru Maekawa, Toru Miyake, Sachiko Kaida, Masatsugu Kojima, Katsushi Takebayashi, Takeshi Sonoda, Masaji Tani   +9 more
wiley   +1 more source

Fimasartan for independent reduction of blood pressure variability in mild-to-moderate hypertension

Drug Design, Development and Therapy, 2016
Mi-Seung Shin,1 Dae Ryong Kang,2 Changsoo Kim,3 Eun Joo Cho,4 Ki-Chul Sung,5 Seok-Min Kang,6 Dong-Soo Kim,7 Seung Jae Joo,8 Seung Hwan Lee,9 Kyung-Kuk Hwang,10 Jeong Bae Park11 1Division of Cardiology, Department of Internal Medicine, Gachon University ...
Shin MS, Kang DR, Kim C, Cho EJ, Sung KC, Kang SM, Kim DS, Joo SJ, Lee SH, Hwang KK, Park JB   +10 more
doaj  

Cardiovascular–Endocrine–Metabolic Medicine: Proposing a New Clinical Sub-Specialty Amid the Cardiometabolic Pandemic

Biomolecules
Cardiovascular–Renal–Hepatic–Metabolic diseases are on the rise worldwide, creating major challenges for patient care and clinical research. Although these conditions share common mechanisms and often respond to similar treatments—such as lifestyle ...
Nikolaos Theodorakis, Maria Nikolaou, Andrew Krentz   +2 more
doaj   +1 more source

IAR‐Net: Tabular Deep Learning Model for Interventionalist's Action Recognition

Advanced Intelligent Systems, EarlyView.
This study presents IAR‐Net, a deep‐learning framework for catheterization action recognition. To ensure optimality, this study quantifies interoperator similarities and differences using statistical tests, evaluates the distribution fidelity of synthetic data produced by six generative models, and benchmarks multiple deep‐learning models.
Toluwanimi Akinyemi, Olatunji Omisore, Wenjing Du, Wenke Duan, Chen Bailang, Liu Kun, Lei Wang, Minxin Wei   +7 more
wiley   +1 more source

Interview: Professor Peter Weissberg, Medical Director of the BHF. [PDF]

, 2016
Dr James Rudd, Heart’s Digital Media Editor, interviewed Professor Peter Weissberg, Medical Director of the British Heart Foundation (BHF), in May 2016. As the largest independent funder of cardiovascular research in the UK (around £100 million annually),
Rudd, James
core   +3 more sources

Synthetic Electrocardiogram Spectrogram Generation Using Generative Adversarial Network‐Based Models: A Comparative Study

Advanced Intelligent Systems, EarlyView.
Cardiovascular diseases are leading death causes; electrocardiogram (ECG) analysis is slow, motivating machine learning and deep learning. This study compares deep convolutional generative adversarial network, conditional GAN, and Wasserstein GAN with gradient penalty (WGAN‐GP) for synthetic ECG spectrograms; Fréchet Inception Distance (FID) and ...
Giovanny Barbosa‐Casanova, Norelli Schettini, Winston Percybrooks, Begoña García‐Zapirain   +3 more
wiley   +1 more source

From bench to bedside and back: translational cardiovascular interventions in veterinary medicine

Advances in Interventional Cardiology
Veterinary interventional cardiology exemplifies the power of reverse translation in cardiovascular medicine. This review examines how procedures initially tested in animal models, refined in human medicine, and subsequently reintroduced to veterinary ...
Sebastian Popiel-Dziewierz, Agnieszka Noszczyk-Nowak, Artur Dziewierz   +2 more
doaj   +1 more source

Building an Intelligent Cardiovascular System Platform: Embedding Artificial Intelligence across All Facets of Cardiovascular Medicine

Advanced Intelligent Systems, EarlyView.
This paper presents an integrated AI‐driven cardiovascular platform unifying multimodal data, predictive analytics, and real‐time monitoring. It demonstrates how artificial intelligence—from deep learning to federated learning—enables early diagnosis, precision treatment, and personalized rehabilitation across the full disease lifecycle, promoting a ...
Mowei Kong, Xingwei Zhao, Qiuting Li, Yang Yu, Chunxiang Zhang   +4 more
wiley   +1 more source