Results 161 to 170 of about 20,506 (324)

Titanium Implants – A Comparison of a Swedish and an Ohio Firm [PDF]

open access: yes
Two firms in the health care market are studied in a case study of the introduction of two almost identical innovations. The two firms, both in the titanium implant business have been chosen so that they match when it comes to origin, technology and ...
Fridh, Ann-Charlotte
core  

Interproximal Distance Analysis of Stereolithographic Casts Made by CAD-CAM Technology: An in Vitro Study [PDF]

open access: yes, 1999
Statement of problem The accuracy of interproximal distances of the definitive casts made by computer-aided design and computer-aided manufacturing (CAD-CAM) technology is not yet known.
Hoffman, Melanie   +2 more
core   +1 more source

Exploring Clinical Decision‐Making in Static Computer‐Assisted Guided Implant Placement: A Survey of Clinicians in Australia and New Zealand

open access: yesAustralian Dental Journal, EarlyView.
ABSTRACT Background Static computer‐assisted guided implant placement (sCAIP) has been shown to enhance accuracy and predictability; however, little is known about the multifactorial decision‐making processes impacting use among clinicians. Methods An exploratory cross‐sectional electronic survey was distributed to implant practitioners across ...
Mathew Amen   +3 more
wiley   +1 more source

Clinical and self‐reported measurements to be included in the core elements of the World Dental Federation's theoretical framework of oral health

open access: yesInternational Dental Journal, EarlyView., 2020
Introduction Oral health is part of general health, and oral diseases share risk factors with several non‐communicable diseases. The World Dental Federation (FDI) has published a theoretical framework illustrating the complex interactions between the core elements of oral health (CEOHs): driving determinants, moderating factors, and general health and ...
Hanna Ahonen   +5 more
wiley   +1 more source

Machine Learning‐Based Prediction of Life‐Threatening Complications During Hemodialysis in Hospitalized Patients With Poor General Conditions

open access: yesArtificial Organs, EarlyView.
A machine learning model using predialysis data predicted sudden events during or after hemodialysis with high accuracy (auROC: 0.889). The key predictors included emergency hospitalization, recent surgery, high heart rate, low albumin levels, and high CRP.
Naotaka Kato   +11 more
wiley   +1 more source

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