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Evaluating the performance of a deep learning-based computer-aided diagnosis (DL-CAD) system for detecting and characterizing lung nodules: Comparison with the performance of double reading by radiologists.

• Authors : Li L; Department of Radiology, National Cancer Center/Cancer Hospital and Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.; Liu Z

Subjects: Deep Learning* ; Early Detection of Cancer*; Diagnosis, Computer-Assisted/Diagnosis, Computer-Assisted/Diagnosis, Computer-Assisted/*methods

• Source: Thoracic cancer [Thorac Cancer] 2019 Feb; Vol. 10 (2), pp. 183-192. Date of Electronic Publication: 2018 Dec 08.Publisher: Wiley Publishing Asia Pty Ltd Country of Publication: Singapore NLM ID: 101531441 Publication Model: Print-Electronic Cited Medium: Internet

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Detection of Cervical Lesion Cell/Clumps Based on Adaptive Feature Extraction.

• Authors : Li, Gang¹ (AUTHOR) ; Li, Xingguang¹ (AUTHOR) ; Wang, Yuting^2,3,4,5 (AUTHOR)

• Source: Bioengineering (Basel). Jul2024, Vol. 11 Issue 7, p686. 15p.

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Systematic Review of Computing Approaches for Breast Cancer Detection Based Computer Aided Diagnosis Using Mammogram Images.

• Authors : Zebari, Dilovan Asaad¹ (AUTHOR); Ibrahim, Dheyaa Ahmed² (AUTHOR); Zeebaree, Diyar Qader³ (AUTHOR)

• Source: Applied Artificial Intelligence. 2021, Vol. 35 Issue 15, p2157-2203. 47p.

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A comparative study of YOLO models and a transformer-based YOLOv5 model for mass detection in mammograms.

• Authors : COŞKUN, Damla^1,2 ; KARABOĞA, Derviş^1,2; BAŞTÜRK, Alper^1,2

• Source: Turkish Journal of Electrical Engineering & Computer Sciences. 2023, Vol. 31 Issue 7, p1294-1313. 20p.

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Advanced diagnostic endoscopy in the upper gastrointestinal tract: Review of the Japan Gastroenterological Endoscopy Society core sessions.

• Authors : Kawai, Takashi¹ (AUTHOR) ; Inoue, Haruhiro² (AUTHOR); Yao, Kenshi³ (AUTHOR)

• Source: Digestive Endoscopy. Sep2023, Vol. 35 Issue 6, p711-717. 7p.

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Computer-aided diagnosis system versus conventional reading system in low-dose (< 2 mSv) computed tomography: comparative study for patients at risk of lung cancer

• Authors : Dong Wang; Lina Cao; Boya Li

Subjects: Diagnostic imaging; Early detection of cancer; Lung neoplasms

• Source: São Paulo Medical Journal (2022)

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A Novel Framework of Manifold Learning Cascade-Clustering for the Informative Frame Selection.

• Authors : Zhang, Lei¹ (AUTHOR) ; Wu, Linjie² (AUTHOR); Wei, Liangzhuang¹ (AUTHOR)

• Source: Diagnostics (2075-4418). Mar2023, Vol. 13 Issue 6, p1151. 22p.

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Evaluation of emphysema on thoracic low-dose CTs through attention-based multiple instance deep learning.

• Authors : Fuhrman, Jordan¹ (AUTHOR) ; Yip, Rowena² (AUTHOR); Zhu, Yeqing² (AUTHOR)

• Source: Scientific Reports. 1/21/2023, Vol. 13 Issue 1, p1-9. 9p.

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Computer-Aided Detection for Pancreatic Cancer Diagnosis: Radiological Challenges and Future Directions.

• Authors : Ramaekers, Mark¹ (AUTHOR) ; Viviers, Christiaan G. A.² (AUTHOR) ; Janssen, Boris V.^3,4 (AUTHOR)

• Source: Journal of Clinical Medicine. Jul2023, Vol. 12 Issue 13, p4209. 15p.

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Retrospective Review of Missed Cancer Detection and Its Mammography Findings with Artificial-Intelligence-Based, Computer-Aided Diagnosis.

• Authors : Park, Ga Eun¹ (AUTHOR) ; Kang, Bong Joo¹ (AUTHOR) ; Kim, Sung Hun¹ (AUTHOR)

• Source: Diagnostics (2075-4418). Feb2022, Vol. 12 Issue 2, p387. 1p.

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