P
Peter Lindholm
Researcher at University of California, San Diego
Publications - 114
Citations - 2127
Peter Lindholm is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Medicine & Internal medicine. The author has an hindex of 21, co-authored 92 publications receiving 1480 citations. Previous affiliations of Peter Lindholm include Karolinska Institutet & Odense University Hospital.
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Journal ArticleDOI
The physiology and pathophysiology of human breath-hold diving.
TL;DR: A brief overview of physiological reactions, limitations, and pathophysiological mechanisms associated with human breath-hold divers can be found in this paper, where the authors also discuss the ability to withstand compressions.
Journal ArticleDOI
Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms
Thomas Schaffter,Diana S. M. Buist,Christoph I. Lee,Yaroslav Nikulin,Dezső Ribli,Yuanfang Guan,William Lotter,Zequn Jie,Hao Du,Sijia Wang,Jiashi Feng,Mengling Feng,Hyo-Eun Kim,F. Albiol,Alberto Albiol,Stephen Morrell,Zbigniew Wojna,Mehmet Eren Ahsen,Umar Asif,Antonio Jimeno Yepes,Shivanthan A.C. Yohanandan,Simona Rabinovici-Cohen,Darvin Yi,Bruce Hoff,Thomas Yu,Elias Chaibub Neto,Daniel L. Rubin,Peter Lindholm,Laurie R. Margolies,Russell B. McBride,Joseph H. Rothstein,Weiva Sieh,Rami Ben-Ari,Stefan Harrer,Andrew D. Trister,Stephen H. Friend,Thea Norman,Berkman Sahiner,Fredrik Strand,Fredrik Strand,Justin Guinney,Gustavo Stolovitzky,Lester Mackey,Joyce Cahoon,Li Shen,Jae Ho Sohn,Hari Trivedi,Yiqiu Shen,Ljubomir Buturovic,Jose Costa Pereira,Jaime S. Cardoso,Eduardo Castro,Karl Trygve Kalleberg,Obioma Pelka,Imane Nedjar,Krzysztof J. Geras,Felix Nensa,Ethan Goan,Sven Koitka,Sven Koitka,Luis Caballero,David D. Cox,Pavitra Krishnaswamy,Gaurav Pandey,Christoph M. Friedrich,Dimitri Perrin,Clinton Fookes,Bibo Shi,Gerard Cardoso Negrie,Michael Kawczynski,Kyunghyun Cho,Can Son Khoo,Joseph Y. Lo,A. Gregory Sorensen,Hwejin Jung +74 more
TL;DR: This diagnostic accuracy study evaluates whether artificial intelligence can overcome human mammography interpretation limits with a rigorous, unbiased evaluation of machine learning algorithms.
Journal ArticleDOI
Effect of Combination of Paracetamol (Acetaminophen) and Ibuprofen vs Either Alone on Patient-Controlled Morphine Consumption in the First 24 Hours After Total Hip Arthroplasty: The PANSAID Randomized Clinical Trial.
Kasper Højgaard Thybo,Daniel Hägi-Pedersen,Jørgen B. Dahl,Jørn Wetterslev,Mariam Nersesjan,Janus Christian Jakobsen,Niels Anker Pedersen,Søren Overgaard,Søren Overgaard,Henrik Morville Schrøder,Harald Schmidt,Jan Gottfrid Bjørck,Kamilla Skovmand,Rune Frederiksen,Morten Buus-Nielsen,Charlotte Voss Sørensen,Laura Smedegaard Kruuse,Peter Lindholm,Ole Mathiesen +18 more
TL;DR: A randomized, blinded, placebo-controlled, 4-group trial in 6 Danish hospitals with 90-day follow-up that included 556 patients undergoing total hip arthroplasty (THA) to investigate beneficial and harmful effects of 4 nonopioid analgesics regimens.
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Effect of artificial intelligence-based triaging of breast cancer screening mammograms on cancer detection and radiologist workload: a retrospective simulation study.
Karin Dembrower,Erik Wåhlin,Yue Liu,Mattie Salim,Mattie Salim,Kevin Smith,Peter Lindholm,Martin Eklund,Fredrik Strand,Fredrik Strand +9 more
TL;DR: Using a commercial AI cancer detector to triage mammograms into no radiologist assessment and enhanced assessment could potentially reduce radiologist workload by more than half, and pre-emptively detect a substantial proportion of cancers otherwise diagnosed later.
Journal ArticleDOI
Comparison of a Deep Learning Risk Score and Standard Mammographic Density Score for Breast Cancer Risk Prediction
Karin Dembrower,Yue Liu,Hossein Azizpour,Martin Eklund,Kevin Smith,Peter Lindholm,Fredrik Strand +6 more
TL;DR: Compared with density-based models, a deep neural network can more accurately predict which women are at risk for future breast cancer, with a lower false-negative rate for more aggressive cancers.