Results 31 to 40 of about 57,851 (263)

B-line quantification: comparing learners novice to lung ultrasound assisted by machine artificial intelligence technology to expert review

The Ultrasound Journal, 2021
Background The goal of this study was to assess the ability of machine artificial intelligence (AI) to quantitatively assess lung ultrasound (LUS) B-line presence using images obtained by learners novice to LUS in patients with acute heart failure (AHF),
Frances M. Russell, Robert R. Ehrman, Allen Barton, Elisa Sarmiento, Jakob E. Ottenhoff, Benjamin K. Nti   +5 more
doaj   +1 more source

Chronobiology of Cancer: How Aging Fuels Oncogenesis at the Molecular Level

Aging and Cancer, EarlyView.
This graphical abstract illustrates the key biological pathways linking aging with cancer development and progression. In the upper left, cumulative exposure to ultraviolet radiation, toxins, and reactive oxygen species (ROS) causes DNA damage and genomic instability, whereas age‐related decline in repair mechanisms, such as ATM/ATR, BER, and NER ...
Anu Singh, Aroonima Misra, Sufian Zaheer
wiley   +1 more source

Enhancement of Chest X-Ray Images to Improve Screening Accuracy Rate Using Iterated Function System and Multilayer Fractional-Order Machine Learning Classifier

IEEE Photonics Journal, 2020
Chest X-ray (CXR) images are usually used to identify the causes of patients’ symptoms, including the classes of lung or heart disorders. In visualization examination, CXR imaging in anterior–posterior (A–P) views is a preliminary ...
Chia-Hung Lin, Jian-Xing Wu, Chien-Ming Li, Pi-Yun Chen, Neng-Sheng Pai, Ying-Che Kuo   +5 more
doaj   +1 more source

Early Clinical, Imaging, and Pathological Characteristics of SRPK3/TTN‐Digenic Myopathy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective SRPK3/TTN‐digenic myopathy was recently established as a skeletal muscle myopathy caused by digenic inheritance. This study characterizes the early clinical presentation of SRPK3/TTN‐digenic myopathy in one previously reported and seven newly identified pediatric patients.
Rotem Orbach, Sandra Donkervoort, Carola Hedberg‐Oldfors, Giovanni Baranello, Dimah Saade, Precilla D'Souza, Ruchee Patel, Eva Michael, A. Reghan Foley, Diana Bharucha‐Goebel, S. Jin Haugland, Meghan McAnally, Omer Abdul Hamid, Katherine Chao, Ellen F. Macnamara, Alan H. Beggs, Anna Sarkozy, Juliane Mueller, Steven A. Moore, Richard S. Finkel, Cynthia J. Tifft, Francesco Muntoni, Anders Oldfors, Carsten G. Bönnemann   +23 more
wiley   +1 more source

Lung disease recognition methods using audio-based analysis with machine learning

Heliyon
The use of computer-based automated approaches and improvements in lung sound recording techniques have made lung sound-based diagnostics even better and devoid of subjectivity errors. Using a computer to evaluate lung sound features more thoroughly with
Ahmad H. Sabry, Omar I. Dallal Bashi, N.H. Nik Ali, Yasir Mahmood Al Kubaisi   +3 more
doaj   +1 more source

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

Arthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos, José Miguel Sequí‐Sabater, Diego Benavent   +2 more
wiley   +1 more source

Cellular Responses to Mechanical Cues Across Scales: From Fundamental Insights to Translational Potential

Advanced Healthcare Materials, EarlyView.
This review examines how cellular behavior is regulated by mechanical cues transmitted through soft biomaterials, from single‐cell mechanosensing to tissue‐level adaptation. It highlights why physiological relevance, rather than model complexity alone, is critical for translational mechanobiology and introduces a scoring framework linking material ...
Mathias Polz, Manuel P. Kainz, Niklas Haider, Theresa Rienmüller, Kerstin Lenk, Rupert Kargl, Michele Terzano, Gerhard Sommer, Gerhard A. Holzapfel, Julia Fuchs   +9 more
wiley   +1 more source

Classification of COVID-19 associated symptomatology using machine learning

Dyna, 2023
The health situation caused by the SARS-Cov2 coronavirus, posed major challenges for the scientific community. Advances in artificial intelligence are a very useful resource, but it is important to determine which symptoms presented by positive cases of
Julian Andres Ramirez-Bautista, Silvia L. Chaparro-Cárdenas , Wilson Gamboa-Contreras, William Guerrero-Salazar , Jorge Adalberto Huerta-Ruelas   +4 more
doaj   +1 more source

A 3D‐Printed Vascular‐Like Perfusion Tumor‐on‐a‐Chip Recapitulates High‐Grade Breast Cancer With in Vivo‐Relevant Drug Resistance

Advanced Healthcare Materials, EarlyView.
A high‐resolution 3D‐printed tumor‐on‐a‐chip platform sustains breast cancer tissues at in vivo–like cell densities through vascular‐like perfusion. This engineered system recapitulates grade‐dependent molecular features and exhibits drug‐resistance profiles that uniquely align with clinically relevant Cmax values.
Geonhui Lee, Bingjie Sun, Nicholas X. Fang, Chunguang Xia   +3 more
wiley   +1 more source

Generative AI Respiratory and Cardiac Sound Separation Using Variational Autoencoders (VAEs)

Computer Sciences & Mathematics Forum
The separation of respiratory and cardiac sounds is a significant challenge in biomedical signal processing due to their overlapping frequency and time characteristics.
Arshad Jamal, R. Kanesaraj Ramasamy, Junaidi Abdullah   +2 more
doaj   +1 more source