Mascarella, Marco A Muthukrishnan, Nikesh Maleki, Farhad Kergoat, Marie-Jeanne Richardson, Keith Mlynarek, Alex Forest, Veronique-Isabelle Reinhold, Caroline Martin, Diego R Hier, Michael
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Published in
The Annals of otology, rhinology, and laryngology
Major postoperative adverse events (MPAEs) following head and neck surgery are not infrequent and lead to significant morbidity. The objective of this study was to ascertain which factors are most predictive of MPAEs in patients undergoing head and neck surgery. A cohort study was carried out based on data from patients registered in the National S...
Guo, Lisa N Lee, Michelle S Kassamali, Bina Mita, Carol Nambudiri, Vinod E
Published in
Journal of the American Academy of Dermatology
Nino, Gustavo Linguraru, Marius G
Published in
Pediatric pulmonology
Piredda, Gian Franco Hilbert, Tom Ravano, Veronica Canales-Rodríguez, Erick Jorge Pizzolato, Marco Meuli, Reto Thiran, Jean-Philippe Richiardi, Jonas Kober, Tobias
Published in
NMR in biomedicine
Long acquisition times preclude the application of multiecho spin echo (MESE) sequences for myelin water fraction (MWF) mapping in daily clinical practice. In search of alternative methods, previous studies of interest explored the biophysical modeling of MWF from measurements of different tissue properties that can be obtained in scan times shorte...
Ruiz, Victor M Goldsmith, Michael P Shi, Lingyun Simpao, Allan F Gálvez, Jorge A Naim, Maryam Y Nadkarni, Vinay Gaynor, J William Tsui, Fuchiang Rich
Published in
The Journal of thoracic and cardiovascular surgery
To develop and evaluate a high-dimensional, data-driven model to identify patients at high risk of clinical deterioration from routinely collected electronic health record (EHR) data. In this single-center, retrospective cohort study, 488 patients with single-ventricle and shunt-dependent congenital heart disease
Wang, R Li, K Y Su, Y-X
Published in
International journal of oral and maxillofacial surgery
The purpose of this study was to investigate whether ameloblastoma with a high likelihood of recurrence can be predicted using random forest model, a machine learning algorithm. Data were collected from patients treated for ameloblastoma between 1999 and 2019 at the University of Hong Kong. Fourteen clinical parameters were used to grow the decisio...
Gofer, Stav Haik, Oren Bardin, Ron Gilboa, Yinon Perlman, Sharon
Published in
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
To evaluate the feasibility of machine learning (ML) tools for segmenting and classifying first-trimester fetal brain ultrasound images. Two image segmentation methods processed high-resolution fetal brain images obtained during the nuchal translucency scan: "Statistical Region Merging" (SRM) and "Trainable Weka Segmentation" (TWS), with training a...
Luvizutto, Gustavo José Silva, Gabrielly Fernanda Nascimento, Monalisa Resende Sousa Santos, Kelly Cristina Appelt, Pablo Andrei de Moura Neto, Eduardo de Souza, Juli Thomaz Wincker, Fernanda Cristina Miranda, Luana Aparecida Hamamoto Filho, Pedro Tadao
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Published in
Topics in stroke rehabilitation
To understand the current practices in stroke evaluation, the main clinical decision support system and artificial intelligence (AI) technologies need to be understood to assist the therapist in obtaining better insights about impairments and level of activity and participation in persons with stroke during rehabilitation. This scoping review maps ...
Kou, Wenjun Galal, Galal Osama Klug, Matthew William Mukhin, Vladislav Carlson, Dustin A Etemadi, Mozziyar Kahrilas, Peter J Pandolfino, John E
Published in
Neurogastroenterology and motility : the official journal of the European Gastrointestinal Motility Society
This study aimed to build and evaluate a deep learning, artificial intelligence (AI) model to automatically classify swallow types based on raw data from esophageal high-resolution manometry (HRM). HRM studies on patients with no history of esophageal surgery were collected including 1,741 studies with 26,115 swallows labeled by swallow type (norma...
Meier, Lukas J Hein, Alice Diepold, Klaus Buyx, Alena
Published in
The American journal of bioethics : AJOB
Machine intelligence already helps medical staff with a number of tasks. Ethical decision-making, however, has not been handed over to computers. In this proof-of-concept study, we show how an algorithm based on Beauchamp and Childress' prima-facie principles could be employed to advise on a range of moral dilemma situations that occur in medical i...