Keyword search (4,164 papers available)

"Machine learning" Keyword-tagged Publications:

Title Authors PubMed ID
1 Sagittal abdominal diameter and abdominal aortic calcification are associated with incident major adverse cardiovascular events: The Manitoba Bone Density Registry Abraha HN; Gebre AK; Sim M; Smith C; Gilani SZ; Ilyas Z; Zarzour F; Schousboe JT; Lix LM; Binkley N; Reid S; Monchka BA; Kimelman D; Lewis JR; Leslie WD; 41903786
ENCS
2 Assessment of PlanetScope Spectral Data for Estimation of Peanut Leaf Area Index Using Machine Learning and Statistical Methods Ekwe M; Fernando H; James G; Adeluyi O; Verrelst J; Kross A; 41682534
CONCORDIA
3 Smart Optogenetics for Real-Time Automated Control of Cardiac Electrical Activity Deng S; Harlaar N; Zhang J; Dekker SO; Kudryashova NN; Zhou H; Bart CI; Jin T; Derevyanko G; van Driel W; Panfilov AV; Poelma RH; de Vries AAF; Zhang G; De Coster T; Pijnappels DA; 41684280
CHEMBIOCHEM
4 Towards smart PFAS management: Integrating artificial intelligence in water and wastewater systems Yaghoobian S; An J; Jeong DW; Hwang JH; 41483514
ENCS
5 New spectral indices for identifying large plastic accumulations in coastal waters with sentinel-2 imagery Wu C; Chen Z; Peng C; An C; 41406508
ENCS
6 Advancements in Magnetorheological Foams: Composition, Fabrication, AI-Driven Enhancements and Emerging Applications Khodaverdi H; Sedaghati R; 40732777
ENCS
7 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
8 Inferring concussion history in athletes using pose and ground reaction force estimation and stability analysis of plyometric exercise videos Alves W; Babouras A; Martineau PA; Schutt D; Robbins S; Fevens T; 40632382
ENCS
9 Statistical or Embodied? Comparing Colorseeing, Colorblind, Painters, and Large Language Models in Their Processing of Color Metaphors Nadler EO; Guilbeault D; Ringold SM; Williamson TR; Bellemare-Pepin A; Com?a IM; Jerbi K; Narayanan S; Aziz-Zadeh L; 40621800
PSYCHOLOGY
10 Application of machine learning for predicting the incubation period of water droplet erosion in metals AlHammad K; Medraj M; Tembely M; 40612685
ENCS
11 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
12 Clustering and Interpretability of Residential Electricity Demand Profiles Kallel S; Amayri M; Bouguila N; 40218540
ENCS
13 Automated abdominal aortic calcification scoring from vertebral fracture assessment images and fall-associated hospitalisations: the Manitoba Bone Mineral Density Registry Sim M; Gebre AK; Dalla Via J; Reid S; Jozani MJ; Kimelman D; Monchka BA; Gilani SZ; Ilyas Z; Smith C; Suter D; Schousboe JT; Lewis JR; Leslie WD; 40080298
ENCS
14 Metrics for evaluation of automatic epileptogenic zone localization in intracranial electrophysiology Hrtonova V; Nejedly P; Travnicek V; Cimbalnik J; Matouskova B; Pail M; Peter-Derex L; Grova C; Gotman J; Halamek J; Jurak P; Brazdil M; Klimes P; Frauscher B; 39608298
SOH
15 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
16 Modelling reindeer rut activity using on-animal acoustic recorders and machine learning Boucher AJ; Weladji RB; Holand Ø; Kumpula J; 38932958
BIOLOGY
17 Post-reinforcement pauses during slot machine gambling are moderated by immersion W Spencer Murch 38429228
PSYCHOLOGY
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 An intelligent decision support system for groundwater supply management and electromechanical infrastructure controls Ataei P; Takhtravan A; Gheibi M; Chahkandi B; Faramarz MG; Waclawek S; Fathollahi-Fard AM; Behzadian K; 38317976
ENCS
20 Machine Learning-Assisted Short-Wave InfraRed (SWIR) Techniques for Biomedical Applications: Towards Personalized Medicine Salimi M; Roshanfar M; Tabatabaei N; Mosadegh B; 38248734
ENCS
21 Editorial: Computational systems immunovirology Zarei Ghobadi M; Teymoori-Rad M; Selvaraj G; Wei DQ; 37475870
CHEMBIOCHEM
22 Class imbalance should not throw you off balance: Choosing the right classifiers and performance metrics for brain decoding with imbalanced data Thölke P; Mantilla-Ramos YJ; Abdelhedi H; Maschke C; Dehgan A; Harel Y; Kemtur A; Mekki Berrada L; Sahraoui M; Young T; Bellemare Pépin A; El Khantour C; Landry M; Pascarella A; Hadid V; Combrisson E; O' Byrne J; Jerbi K; 37385392
IMAGING
23 Prospects of Novel and Repurposed Immunomodulatory Drugs against Acute Respiratory Distress Syndrome (ARDS) Associated with COVID-19 Disease Nayak SS; Naidu A; Sudhakaran SL; Vino S; Selvaraj G; 37109050
CHEMBIOCHEM
24 Comparison of photocatalysis and photolysis of 2,2,4,4-tetrabromodiphenyl ether (BDE-47): Operational parameters, kinetic studies, and data validation using three modern machine learning models Motamedi M; Yerushalmi L; Haghighat F; Chen Z; Zhuang Y; 36907486
ENCS
25 Using machine learning to retrospectively predict self-reported gambling problems in Quebec Murch WS; Kairouz S; Dauphinais S; Picard E; Costes JM; French M; 36880253
SOCANTH
26 Unique Photoactivated Time-Resolved Response in 2D GeS for Selective Detection of Volatile Organic Compounds Mohammadzadeh MR; Hasani A; Jaferzadeh K; Fawzy M; De Silva T; Abnavi A; Ahmadi R; Ghanbari H; Askar A; Kabir F; Rajapakse RKND; Adachi MM; 36658730
PHYSICS
27 Optimizing Biodegradable Starch-Based Composite Films Formulation for Wound-Dressing Applications Delavari MM; Ocampo I; Stiharu I; 36557445
ENCS
28 Impact from the evolution of private vehicle fleet composition on traffic related emissions in the small-medium automotive city Tian X; Huang G; Song Z; An C; Chen Z; 35709991
ENCS
29 Weakly Supervised Occupancy Prediction Using Training Data Collected via Interactive Learning Bouhamed O; Amayri M; Bouguila N; 35590880
ENCS
30 Maternal exposure to black carbon and nitrogen dioxide during pregnancy and birth weight: Using machine-learning methods to achieve balance in inverse-probability weights Dong S; Abu-Awad Y; Kosheleva A; Fong KC; Koutrakis P; Schwartz JD; 35227679
PSYCHOLOGY
31 On the Impact of Biceps Muscle Fatigue in Human Activity Recognition. Elshafei M, Costa DE, Shihab E 33557239
ENCS
32 Towards Detecting Biceps Muscle Fatigue in Gym Activity Using Wearables. Elshafei M, Shihab E 33498702
ENCS
33 Designing a hybrid reinforcement learning based algorithm with application in prediction of the COVID-19 pandemic in Quebec. Khalilpourazari S, Hashemi Doulabi H 33424076
ENCS
34 Integrative approach for detecting membrane proteins. Alballa M, Butler G 33349234
CSFG
35 Understanding the temporal evolution of COVID-19 research through machine learning and natural language processing. Ebadi A; Xi P; Tremblay S; Spencer B; Pall R; Wong A; 33230352
ENCS
36 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
37 Hybrid multi-mode machine learning-based fault diagnosis strategies with application to aircraft gas turbine engines. Shen Y, Khorasani K 32673847
ENCS

 

Title:Maternal exposure to black carbon and nitrogen dioxide during pregnancy and birth weight: Using machine-learning methods to achieve balance in inverse-probability weights
Authors:Dong SAbu-Awad YKosheleva AFong KCKoutrakis PSchwartz JD
Link:https://pubmed.ncbi.nlm.nih.gov/35227679/
DOI:10.1016/j.envres.2022.112978
Publication:Environmental research
Keywords:Birth weightBlack carbonCausal methodMachine learningNitrogen dioxidePropensity score
PMID:35227679 Category: Date Added:2022-03-01
Dept Affiliation: PSYCHOLOGY
1 Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, USA. Electronic address: shuxindong@hsph.harvard.edu.
2 Department of Psychology, Concordia University, Montreal, Canada.
3 Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, USA.
4 School of the Environment, Yale University, New Haven, USA.
5 Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, USA.

Description:

Background: Low birth weight is associated with increased risks of health problems in infancy and later life. Among the epidemiological analyses suggesting an association between air pollution and birth weight, few have estimated the effects of black carbon (BC) or together with nitrogen dioxide (NO2), and even fewer studies have used causal modelling.

Methods: We examined 1,119,011 birth records between 2001/01/01 and 2015/12/31 from the Massachusetts Birth Registry to investigate causal associations between prenatal exposure to BC and NO2 and birth weight. We calculated mean residential BC and NO2 exposures 0-30, and 31-280 days prior to birth from validated spatial-temporal models. We fit generalized propensity score models with gradient boosting tuned by a new algorithm to achieve covariate balance, then fit marginal structural models with stabilized inverse-probability weights.

Results: Throughout pregnancy, the average birth weight would drop by 17.0 g (95% CI: 15.4, 18.6) for an IQR increase of 0.14 µg/m3 in BC and would independently drop by 19.9 g (95% CI: 18.6, 21.3) for an IQR increase of 9.8 ppb in NO2. Most of the negative effects of BC on birth weight are from 0 to 30 days before the delivery date. The estimated odds ratio of low birth weight for every IQR increase during the entire pregnancy was 1.131 (95% CI: 1.106, 1.156) for BC and 1.082 (95% CI: 1.062, 1.103) for NO2.

Conclusions: We found that prenatal exposures to both BC and NO2 were associated with lower birth weight.





BookR developed by Sriram Narayanan
for the Concordia University School of Health
Copyright © 2011-2026
Cookie settings
Concordia University