6 results
Search Results
2. ACM Publications Finances for 2022: Striving for Balance between Mission, Sustainability, and Growth.
- Author
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HALL, WENDY, SRIVASTAVA, DIVESH, and DELMAN, SCOTT
- Subjects
COMPUTER science periodicals ,SCHOLARLY publishing ,OPEN access publishing - Abstract
The article discusses the Association for Computing Machinery's (ACM's) plan to convert many of its publications to an open-access (OA) model. Publications mentioned include the International Conference Proceedings Series. The authors discuss how the change will affect the ACM's finances.
- Published
- 2024
- Full Text
- View/download PDF
3. Artificial intelligence and dental panoramic radiographs: where are we now?
- Author
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Webster, Scott and Fraser, Jacqueline
- Subjects
ARTIFICIAL intelligence ,RADIOGRAPHS ,MEDICAL databases ,DENTAL radiography ,DENTAL caries ,DATA extraction ,DENTAL technology - Abstract
Data sources: Bielefeld Academic Search Engine (BASE), Google Scholar Association for Computing Machinery: Guide to Computing Literature (ACM) and National Library of Medicine: PubMed databases were searched for systematic reviews. Study selection: This study addressed a structured PICO question (Population, Intervention, Comparison, Outcome). Population was panoramic radiographs in human subjects. Intervention was use of artificial intelligence (AI) diagnostics, compared to human-only diagnosis. Quantitative or qualitative AI efficiency was the outcome. Systematic reviews were considered if they stated 'systematic review' in their title or abstract, were published in English and were not bound by a certain time frame. No supplemental primary studies were included. Screening and removal of duplicates were performed using the Rayyan tool. Data extraction and synthesis: Data were extracted from each systematic review by two authors, with a third author having the deciding vote in cases of inconsistency. Cohen's Kappa co-efficient was used to measure reliability between authors, resulting in almost perfect agreement. The risk of bias was accounted for using the ROBIS method which resulted in one paper being rejected, so only 11 included in results. Data were then grouped into seven domains which were detected by AI: teeth identification and numbering, detection of periapical lesions, periodontal bone loss, osteoporosis, maxillary sinusitis, dental caries, and other tasks. The effectiveness of the AI systems was assessed by various outcome metrics - accuracy, sensitivity, specificity, and precision being the most common variables. Results: Results of this overview show a significant increase in accuracy of AI in analysing OPTs between 1988-2023. Latest AI models are most accurate in teeth identification and numbering (93.67%) whilst caries detection and osteoporosis showed 91.5% and 89.29% accuracy, respectively. Accurate results were also observed for the detection of maxillary sinusitis and periodontal bone loss. However, given the heterogeneity of source studies used in these systematic reviews, results should be interpreted with caution. Conclusions: With improving AI technology, its use in dental radiology can be increasingly effective in supporting dentists in the detection of different pathologies. This overview has shown that systematic reviews of AI can quickly become outdated and that results of any systematic review should be treated with caution as this field advances. As such, regular updating and ongoing research is required. [ABSTRACT FROM AUTHOR]
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- 2024
- Full Text
- View/download PDF
4. Sensor-based systems for the measurement of Functional Reach Test results: a systematic review.
- Author
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Francisco, Luís, Duarte, João, Nunes Godinho, António, Zdravevski, Eftim, Albuquerque, Carlos, Pires, Ivan Miguel, and Coelho, Paulo Jorge
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SCIENCE databases ,DATABASE industry ,PHYSICAL therapy ,CONGREGATE housing ,STATISTICAL models - Abstract
The measurement of Functional Reach Test (FRT) is a widely used assessment tool in various fields, including physical therapy, rehabilitation, and geriatrics. This test evaluates a person's balance, mobility, and functional ability to reach forward while maintaining stability. Recently, there has been a growing interest in utilizing sensor-based systems to objectively and accurately measure FRT results. This systematic review was performed in various scientific databases or publishers, including PubMed Central, IEEE Explore, Elsevier, Springer, the Multidisciplinary Digital Publishing Institute (MDPI), and the Association for Computing Machinery (ACM), and considered studies published between January 2017 and October 2022, related to methods for the automation of the measurement of the Functional Reach Test variables and results with sensors. Camera-based devices and motion-based sensors are used for Functional Reach Tests, with statistical models extracting meaningful information. Sensor-based systems offer several advantages over traditional manual measurement techniques, as they can provide objective and precise measurements of the reach distance, quantify postural sway, and capture additional parameters related to the movement. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
5. ACM Names Recipients of Gordon Bell, Climate Modelling Awards.
- Subjects
COMPUTER science awards ,ATMOSPHERIC models - Abstract
The article announces the winners of two 2023 Association for Computing Machinery (ACM) prizes: the Gordon Bell Prize, given to several researchers for their joint project entitled "Large-Scale Materials Modeling at Quantum Accuracy: Ab Initio Simulations of Quasicrystals and Interacting Extended Defects in Metallic Alloys," and the Gordon Bell Prize for Climate Modelling, given to several researchers for their joint project entitled "The Simple Cloud-Resolving E3SM Atmosphere Model Running on the Frontier Exascale System."
- Published
- 2024
- Full Text
- View/download PDF
6. Amanda Randles awarded ACM Prize in Computing for revolutionizing medical diagnostics.
- Subjects
AWARDS ,CAREER development ,MEDICAL sciences ,MACHINE learning ,COMPUTERS in education - Abstract
Amanda Randles, an associate professor at Duke University's Pratt School of Engineering, has been awarded the ACM Prize in Computing for her groundbreaking contributions to computational health. Randles has developed innovative algorithms and tools that utilize supercomputers to create highly precise simulations of biophysical processes, including blood flow and cancer cell movement. Her work has direct applications in patient care and has the potential to revolutionize medical diagnostics. The ACM Prize in Computing recognizes early-to-mid-career computer scientists whose research has broad implications and fundamental impact. [Extracted from the article]
- Published
- 2024
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