The Use of Artificial Intelligence in Diagnostic Medical Imaging: Systematic Literature Review

Hafizovic, Lamija; Čaušević, Aldijana; Deumić, Amar; Bećirović, Lemana Spahić; Pokvić, Lejla Gurbeta; Badnjević, Almir

doi:10.1109/bibe52308.2021.9635307

Cited by 21 publications

(6 citation statements)

References 37 publications

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“…The small sample size and the incomplete information about full protection or protocol of protection of COVID-19 [44,45] are the major limitations of the current study.…”

Section: Discussionmentioning

confidence: 94%

Clinical management and infection control protocols during the COVID-19 pandemic: An online survey

Rafeeq

Saleem

Nahidh

et al. 2023

THC

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BACKGROUND: SARS-CoV-2 (COVID-19) is considered a highly infectious and life threatening disease. OBJECTIVE: The present paper aims to evaluate various aspects of preventive measures and clinical management of the scheduled visits for orthodontic patients to the dental clinics during the outbreak of COVID-19, and to assess how orthodontists dealt with this challenge. METHODS: Orthodontists in private and public clinics were invited to fill a questionnaire that addressed infection control protocols and concerns about clinical management of patients in the clinics during the pandemic. Frequncies and percentages of the responses were obtained and compared using Chi-square tests. RESULTS: About 77% of those working in private clinics, and 63% of those working in private and governmental clinics performed room disinfection following each patient. In case of patients needing urgent management and have active infection, 56% of the participants provided care under high infection control measures; on the contrary, 64% provided symptomatic intervention including orthodontic wax, analgesics and sometimes mouthwash. CONCLUSION: The COVID-19 pandemic has had a negative impact on the orthodontic treatments. All pre-cautionary measures have to be made available in the clinic in order to minimize the spread of viral infection with continuous dental health care training.

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“…The small sample size and the incomplete information about full protection or protocol of protection of COVID-19 [44,45] are the major limitations of the current study.…”

Section: Discussionmentioning

confidence: 94%

Clinical management and infection control protocols during the COVID-19 pandemic: An online survey

Rafeeq

Saleem

Nahidh

et al. 2023

THC

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“…To locate the conus medullaris through ultrasound remains a challenge, the failure always results from the difficulty to capture image due to fetal movement [ 15 ], which leads to time waste and unnecessary energy consumption of the physicians. AI presents superior advantages in the process of its rapid development [ 16 , 17 ], in the field of obstetry, the applications of AI in the recognition of medical images detected by ultrasound and the measurements of obstetric parameters have become increasingly apparent [ 18 ].…”

Section: Discussionmentioning

confidence: 99%

Ultrasound-based horizontal ranging in the localization of fetal conus medullaris

Liu,

Li,

Yang

et al. 2024

THC

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BACKGROUND: Currently, there are a variety of methods for ultrasound to localize the conus medullaris. A concern is that measured values can be influenced by variations in spinal flexion and extension. OBJECTIVE: To overcome this limitation, the present study measures the horizontal distance (HD) between the end of the conus medullaris and the caudal edge of last vertebral body ossification in normal fetus at different gestational weeks, and analyzes the relationship between the measured value and fetal growth, as well as the utility of these measurements in assessing the position of the conus medullaris. METHODS: A total of 655 fetuses at gestational weeks 18–40, who underwent routine prenatal ultrasound, were selected in the study. We measured the distance between the end of the cone of the fetal spinal cord and the caudal end of the final vertebral ossification center (Distance1, D1), the distance between the end of the spinal cord cone and the intersection of the extension of D1 with the caudal skin (Distance2, D2), and HD. We analyzed the correlation between the measurements and gestational weeks, established normal reference values, the ratio of D1, D2 and HD to the commonly used growth parameters was calculated. The ratios of D1, D2, HD and the application value of each ratio phase were analyzed, and the reliability analysis of repeated measurement results among physicians was performed. RESULTS: D1, D2 and HD exhibited strong linear correlations with gestational weeks. Among the ratios of D1, D2 and HD to common growth parameters, D2/FL stabilized after 20 weeks of gestation and consistently exceeded 1. Repeatability tests between D1, D2 and HD showed good reliability (P> 0.05). CONCLUSION: D1, D2 and HD are significantly correlated with gestational age. Horizontal distance measurement can effectively determine the position of fetal conus medullaris, enabling rapid prenatal evaluation of low position of conus medullaris and excluding the possibility of tethered cord.

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“…Bir çalışmada makine öğrenmesi teknikleri kullanılarak diyabet ve kardiyovasküler hastalıkların teşhisi [7], yapay sinir ağı kullanılarak epileptik nöbet sınıflandırması [8], prostat dokularının sınıflandırılması [9], stres sınıflandırması [10] veya yapay zeka ile yapılan kardiyoloji çalışmaları verilebilir [11]. Yapay sinir ağı, makine öğrenmesi veya yapay zeka metotları sağlık alanında başarılı modeller oluşturmak için giderek daha fazla kullanılmaktadır [12][13][14][15]. Ses analizi üzerine yapılan bir çalışmada; 57 sağlıklı 150 patolojik olarak etiketlenmiş popülasyon YSA (Yapay Sinir Ağı) kullanarak sınıflandırılmıştır.…”

Section: Deneysel Metot (Experimental Method)unclassified

Karaciğer enzimlerinden hastalık tahmini için yapay sinir ağları ve sezgisel yöntem modellerinin performansları: Biyokimya cihazı çıktılarına uygulanması

Çavga

2024

Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi

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Karar verme sistemlerinin sağlık alanında uygulanmasında, gelişen teknolojiyle birlikte, direkt analiz cihazı çıktıları kullanılabilir hale gelmiştir. Veri setinin genişlemesiyle birlikte modellerin doğrulukları da artmaktadır. Bu çalışmada kullanılan veri seti parametreleri nicelik ve nitelik yönünden eski çalışmalara kıyasla gerçek duruma daha yakın ham veriler içermektedir. Karaciğer hastalıklarını tanımlamak için kurulan modeller incelendiğinde uzman görüşü içeren parametreler kullanılması sebebiyle model performansının yanında uzman performansının da etkisi olduğu görülmektedir. Bu çalışmada kullanılan veri seti sınıf değerleri dışında sübjektif verilere yer vermeyerek uzman görüşünü sadece modelin eğitiminde kullanmıştır. Bu sayede model performansının veri setine diğer çalışmalardan daha az bağımlı olacaktır. Gerçek hayat verileri farklı modeller ile çalışılarak, hangi yapıların daha iyi olduğu görülmüştür. Çalışmada yapay sinir ağları ve parçacık sürü optimizasyonu metotları sınıflandırma problemini çözebilmek için eğitilmiş ve test verileri ile sınanarak sonuçlar analiz edilmiştir.

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The Use of Artificial Intelligence in Diagnostic Medical Imaging: Systematic Literature Review

Cited by 21 publications

References 37 publications

Clinical management and infection control protocols during the COVID-19 pandemic: An online survey

Clinical management and infection control protocols during the COVID-19 pandemic: An online survey

Ultrasound-based horizontal ranging in the localization of fetal conus medullaris

Karaciğer enzimlerinden hastalık tahmini için yapay sinir ağları ve sezgisel yöntem modellerinin performansları: Biyokimya cihazı çıktılarına uygulanması

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