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:Evaluation of the Diet Tracking Smartphone Application Keenoa™: A Qualitative Analysis
Authors:Bouzo VPlourde HBeckenstein HCohen TR
Link:https://pubmed.ncbi.nlm.nih.gov/34582258/
DOI:10.3148/cjdpr-2021-022
Publication:Canadian journal of dietetic practice and research : a publication of Dietitians of Canada = Revue canadienne de la pratique et de la recherche en dietetique : une publication des Dietetistes du Canada
Keywords:Mobile applicationsapplications mobilesartificial intelligencediet recordsintelligence artificiellejournal alimentairenutrition assessmentévaluation nutritionnelle
PMID:34582258 Category: Date Added:2021-09-28
Dept Affiliation: PERFORM
1 School of Human Nutrition, McGill University, Montreal, QC.
2 PERFORM Centre, Concordia University, Montreal, QC.
3 Faculty of Land and Food Systems, Food, Nutrition and Health, University of British Columbia, Vancouver, BC.

Description:

Keenoa™ is a novel Canadian diet application (app) currently used by Canadian dietitians to collect diet-related data from clients. The goal of this study was to evaluate Keenoa™ based on user feedback and compare it to a conventional pen and paper method. One hundred and two participants were recruited and randomly assigned to record their diets using this application for 3 nonconsecutive days. Following this, participants were invited to complete an online "exit" survey. Seventy-two subjects responded, with 50 completing an open-ended question asking for general feedback about the app. Data were reviewed and 3 main themes emerged: strengths, challenges, and future recommendations. Strengths associated with the app consisted of picture recognition software, the additional commentary feature, and the overall pleasant data collection process. Challenges that were identified included inconsistencies with the barcode scanning features, the limited food database, time to enter food details, and software issues. Future recommendations included using a larger food database, pairing dietary intake with physical activity monitoring, and having accessible nutritional data. Despite these limitations, participants preferred using mobile apps to record diet compared with traditional written food diaries.





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