| Keyword search (4,163 papers available) | ![]() |
"artificial intelligence" Keyword-tagged Publications:
| Title | Authors | PubMed ID | |
|---|---|---|---|
| 1 | Editorial: Data-driven vaccine design for microbial-associated diseases | Selvaraj G; Kaliamurthi S; Wei D; | 41624882 CHEMBIOCHEM |
| 2 | Divergent creativity in humans and large language models | Bellemare-Pepin A; Lespinasse F; Thölke P; Harel Y; Mathewson K; Olson JA; Bengio Y; Jerbi K; | 41565675 PSYCHOLOGY |
| 3 | Towards smart PFAS management: Integrating artificial intelligence in water and wastewater systems | Yaghoobian S; An J; Jeong DW; Hwang JH; | 41483514 ENCS |
| 4 | Automated abdominal aortic calcification and trabecular bone score independently predict incident fracture during routine osteoporosis screening | Gebre AK; Sim M; Gilani SZ; Saleem A; Smith C; Hans D; Reid S; Monchka BA; Kimelman D; Jozani MJ; Schousboe JT; Lewis JR; Leslie WD; | 41071096 ENCS |
| 5 | Deep learning-based feature discovery for decoding phenotypic plasticity in pediatric high-grade gliomas single-cell transcriptomics | Abicumaran Uthamacumaran | 40848317 PSYCHOLOGY |
| 6 | Evolution from the physical process-based approaches to machine learning approaches to predicting urban floods: a literature review | Md Shike Bin Mazid Anik | 40692624 ENCS |
| 7 | Comprehensive review of reinforcement learning for medical ultrasound imaging | Elmekki H; Islam S; Alagha A; Sami H; Spilkin A; Zakeri E; Zanuttini AM; Bentahar J; Kadem L; Xie WF; Pibarot P; Mizouni R; Otrok H; Singh S; Mourad A; | 40567264 ENCS |
| 8 | Emerging Image-Guided Navigation Techniques for Cardiovascular Interventions: A Scoping Review | Roshanfar M; Salimi M; Jang SJ; Sinusas AJ; Kim J; Mosadegh B; | 40428106 ENCS |
| 9 | Machine learning innovations in CPR: a comprehensive survey on enhanced resuscitation techniques | Islam S; Rjoub G; Elmekki H; Bentahar J; Pedrycz W; Cohen R; | 40336660 ENCS |
| 10 | Advanced Robotics for the Next-Generation of Cardiac Interventions | Roshanfar M; Salimi M; Kaboodrangi AH; Jang SJ; Sinusas AJ; Wong SC; Mosadegh B; | 40283240 ENCS |
| 11 | The Present and Future of Adult Entertainment: A Content Analysis of AI-Generated Pornography Websites | Lapointe VA; Dubé S; Rukhlyadyev S; Kessai T; Lafortune D; | 40032709 PSYCHOLOGY |
| 12 | MuscleMap: An Open-Source, Community-Supported Consortium for Whole-Body Quantitative MRI of Muscle | McKay MJ; Weber KA; Wesselink EO; Smith ZA; Abbott R; Anderson DB; Ashton-James CE; Atyeo J; Beach AJ; Burns J; Clarke S; Collins NJ; Coppieters MW; Cornwall J; Crawford RJ; De Martino E; Dunn AG; Eyles JP; Feng HJ; Fortin M; Franettovich Smith MM; Galloway G; Gandomkar Z; Glastras S; Henderson LA; Hides JA; Hiller CE; Hilmer SN; Hoggarth MA; Kim B; Lal N; LaPorta L; Magnussen JS; Maloney S; March L; Nackley AG; O' Leary SP; Peolsson A; Perraton Z; Pool-Goudzwaard AL; Schnitzler M; Seitz AL; Semciw AI; Sheard PW; Smith AC; Snodgrass SJ; Sullivan J; Tran V; Valentin S; Walton DM; Wishart LR; Elliott JM; | 39590726 HKAP |
| 13 | Cell Fate Dynamics Reconstruction Identifies TPT1 and PTPRZ1 Feedback Loops as Master Regulators of Differentiation in Pediatric Glioblastoma-Immune Cell Networks | Abicumaran Uthamacumaran | 39420135 PSYCHOLOGY |
| 14 | Recommendations on the use of artificial intelligence in health promotion | Smith A; Arena R; Bacon SL; Faghy MA; Grazzi G; Raisi A; Vermeesch AL; Ong' wen M; Popovic D; Pronk NP; | 39389332 HKAP |
| 15 | Education in Laparoscopic Cholecystectomy: Design and Feasibility Study of the LapBot Safe Chole Mobile Game | Noroozi M; St John A; Masino C; Laplante S; Hunter J; Brudno M; Madani A; Kersten-Oertel M; | 39052314 ENCS |
| 16 | LapBot-Safe Chole: validation of an artificial intelligence-powered mobile game app to teach safe cholecystectomy | St John A; Khalid MU; Masino C; Noroozi M; Alseidi A; Hashimoto DA; Altieri M; Serrot F; Kersten-Oertal M; Madani A; | 39009730 ENCS |
| 17 | Who Should Decide How Machines Make Morally Laden Decisions? | Dominic Martin | 27905083 JMSB |
| 18 | The State of Artificial Intelligence in Skin Cancer Publications | Joly-Chevrier M; Nguyen AX; Liang L; Lesko-Krleza M; Lefrançois P; | 38323537 ENCS |
| 19 | Performance of ChatGPT on a Practice Dermatology Board Certification Examination | Joly-Chevrier M; Nguyen AX; Lesko-Krleza M; Lefrançois P; | 37489920 ENCS |
| 20 | Dissecting cell fate dynamics in pediatric glioblastoma through the lens of complex systems and cellular cybernetics | Abicumaran Uthamacumaran | 35678918 PHYSICS |
| 21 | The Algorithms of Mindfulness | Johannes Bruder | 35103028 CONCORDIA |
| 22 | Evaluation of the Diet Tracking Smartphone Application Keenoa™: A Qualitative Analysis | Bouzo V; Plourde H; Beckenstein H; Cohen TR; | 34582258 PERFORM |
| 23 | Osseointegration Pharmacology: A Systematic Mapping Using Artificial Intelligence | Mahri M; Shen N; Berrizbeitia F; Rodan R; Daer A; Faigan M; Taqi D; Wu KY; Ahmadi M; Ducret M; Emami E; Tamimi F; | 33181361 CONCORDIA |
| Title: | Automated abdominal aortic calcification and trabecular bone score independently predict incident fracture during routine osteoporosis screening | ||||
| Authors: | Gebre AK, Sim M, Gilani SZ, Saleem A, Smith C, Hans D, Reid S, Monchka BA, Kimelman D, Jozani MJ, Schousboe JT, Lewis JR, Leslie WD | ||||
| Link: | https://pubmed.ncbi.nlm.nih.gov/41071096/ | ||||
| DOI: | 10.1093/jbmr/zjaf144 | ||||
| Publication: | Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research | ||||
| Keywords: | Dual-energy x-ray absorptiometry; artificial intelligence; bone mineral density; bone texture; fracture; vascular calcification; | ||||
| PMID: | 41071096 | Category: | Date Added: | 2025-10-10 | |
| Dept Affiliation: |
ENCS
1 Nutrition & Health Innovation Research Institute, School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia. 2 Medical School, The University of Western Australia, Perth, WA, Australia. 3 Centre for AI & ML, School of Science, Edith Cowan University, Perth, Australia. 4 Computer Science and Software Engineering, The University of Western Australia, Perth, Australia. 5 Bone and Joint Department, Lausanne University Hospital, Lausanne, Switzerland. 6 Department of Computer Science, Concordia University, Montreal, Canada. 7 George and Fay Yee Centre for Healthcare Innovation, University of Manitoba, Winnipeg, Canada. 8 Department of Radiology, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Canada. 9 Department of Statistics, University of Manitoba, Winnipeg, Canada. 10 Park Nicollet Clinic and HealthPartners Institute, HealthPartners, Minneapolis, USA. 11 Division of Health Policy and Management, University of Minnesota, Minneapolis, USA. 12 Department of Internal Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Canada. |
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Description: |
Abdominal aortic calcification (AAC), a marker of subclinical cardiovascular disease, has previously shown to be associated with low bone mineral density (BMD) and fracture. However, it remains unclear whether AAC is associated with trabecular bone score (TBS), a gray-level textural measure, or whether it predicts fracture risk independent of this measure. Here, we examined the cross-sectional association of AAC scored using a validated machine learning algorithm (ML-AAC24) with TBS, and their simultaneous associations with incident fractures in 7,691 individuals (93.4% women) through the Manitoba BMD Registry (mean age 75.3 years). The association between ML-AAC24 and TBS was tested using generalised linear regression. Cox proportional hazards models tested the simultaneous relationships of ML-AAC24 and TBS with incident fractures. At baseline, 41.3% of the study cohort had low (<2), 32.4% had moderate (2 to <6) and 26.3% had high (=6) ML-AAC24. Compared to low ML-AAC24, high ML-AAC24 was associated with a 0.81% lower TBS in the multivariable-adjusted model. Independent of each other and multiple established fracture risk factors, ML-AAC24 and TBS were each associated with an increased risk of incident fractures. Specifically, high ML-AAC24 (HR 1.41 95%CI 1.15-1.73, compared to low ML-AAC24) and lower TBS (HR 1.13 95%CI 1.05-1.22, per SD decrease) were associated with increased relative hazards for any incident fracture. High ML-AAC24 and lower TBS were also associated with incident major osteoporotic fracture (HR 1.48 95%CI 1.18-1.87 and HR 1.15 95%CI 1.06-1.25, respectively) and hip fracture (HR 1.56 95%CI 1.05-2.31 and HR 1.25 95%CI 1.08-1.44, respectively). In conclusion, high ML-AAC24 is associated with lower TBS in older adults attending routine osteoporosis screening. Both measures were associated with incident fractures. The findings of this study highlight high ML-AAC24, seen in more than 1 in 4 of the study cohort, and lower TBS provide complementary prognostic information for fracture risk. |



