Kunio Doi to Diagnosis, Differential
This is a "connection" page, showing publications Kunio Doi has written about Diagnosis, Differential.
Connection Strength
1.113
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Presentation of similar images as a reference for distinction between benign and malignant masses on mammograms: analysis of initial observer study. J Digit Imaging. 2010 Oct; 23(5):592-602.
Score: 0.066
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Potential usefulness of similar images in the differential diagnosis of clustered microcalcifications on mammograms. Radiology. 2009 Dec; 253(3):625-31.
Score: 0.065
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Differentiation of common large sellar-suprasellar masses effect of artificial neural network on radiologists' diagnosis performance. Acad Radiol. 2009 Mar; 16(3):313-20.
Score: 0.063
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Improving radiologists' recommendations with computer-aided diagnosis for management of small nodules detected by CT. Acad Radiol. 2006 Aug; 13(8):943-50.
Score: 0.052
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Computer-aided diagnosis for the detection and classification of lung cancers on chest radiographs ROC analysis of radiologists' performance. Acad Radiol. 2006 Aug; 13(8):995-1003.
Score: 0.052
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How can a massive training artificial neural network (MTANN) be trained with a small number of cases in the distinction between nodules and vessels in thoracic CT? Acad Radiol. 2005 Oct; 12(10):1333-41.
Score: 0.049
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Current status and future potential of computer-aided diagnosis in medical imaging. Br J Radiol. 2005; 78 Spec No 1:S3-S19.
Score: 0.047
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Radiologists' performance for differentiating benign from malignant lung nodules on high-resolution CT using computer-estimated likelihood of malignancy. AJR Am J Roentgenol. 2004 Nov; 183(5):1209-15.
Score: 0.046
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Malignant versus benign nodules at CT screening for lung cancer: comparison of thin-section CT findings. Radiology. 2004 Dec; 233(3):793-8.
Score: 0.046
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Overview on research and development of computer-aided diagnostic schemes. Semin Ultrasound CT MR. 2004 Oct; 25(5):404-10.
Score: 0.046
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Computer-aided diagnosis in chest radiology. Semin Ultrasound CT MR. 2004 Oct; 25(5):432-7.
Score: 0.046
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Artificial neural networks (ANNs) for differential diagnosis of interstitial lung disease: results of a simulation test with actual clinical cases. Acad Radiol. 2004 Jan; 11(1):29-37.
Score: 0.044
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Quantitative computerized analysis of diffuse lung disease in high-resolution computed tomography. Med Phys. 2003 Sep; 30(9):2440-54.
Score: 0.043
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Computer-aided diagnosis to distinguish benign from malignant solitary pulmonary nodules on radiographs: ROC analysis of radiologists' performance--initial experience. Radiology. 2003 May; 227(2):469-74.
Score: 0.042
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Computer-aided diagnosis in chest radiography: results of large-scale observer tests at the 1996-2001 RSNA scientific assemblies. Radiographics. 2003 Jan-Feb; 23(1):255-65.
Score: 0.041
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Automated computerized scheme for distinction between benign and malignant solitary pulmonary nodules on chest images. Med Phys. 2002 May; 29(5):701-8.
Score: 0.039
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Usefulness of an artificial neural network for differentiating benign from malignant pulmonary nodules on high-resolution CT: evaluation with receiver operating characteristic analysis. AJR Am J Roentgenol. 2002 Mar; 178(3):657-63.
Score: 0.038
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Cerebellar myxoid type meningioma in a Shih Tzu dog. J Vet Med Sci. 2002 Feb; 64(2):155-7.
Score: 0.038
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Esophageal adenosquamous carcinoma in a cat. J Vet Med Sci. 2001 Jan; 63(1):91-3.
Score: 0.036
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Effect of an artificial neural network on radiologists' performance in the differential diagnosis of interstitial lung disease using chest radiographs. AJR Am J Roentgenol. 1999 May; 172(5):1311-5.
Score: 0.032
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Artificial neural networks in chest radiography: application to the differential diagnosis of interstitial lung disease. Acad Radiol. 1999 Jan; 6(1):2-9.
Score: 0.031
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Automated computerized classification of malignant and benign masses on digitized mammograms. Acad Radiol. 1998 Mar; 5(3):155-68.
Score: 0.029
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Malignant and benign clustered microcalcifications: automated feature analysis and classification. Radiology. 1996 Mar; 198(3):671-8.
Score: 0.025
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Representation of lesion similarity by use of multidimensional scaling for breast masses on mammograms. J Digit Imaging. 2013 Aug; 26(4):740-7.
Score: 0.021
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True detection versus "accidental" detection of small lung cancer by a computer-aided detection (CAD) program on chest radiographs. J Digit Imaging. 2010 Feb; 23(1):66-72.
Score: 0.016
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Usefulness of texture analysis for computerized classification of breast lesions on mammograms. J Digit Imaging. 2007 Sep; 20(3):248-55.
Score: 0.014
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Usefulness of artificial neural network for differential diagnosis of hepatic masses on CT images. Acad Radiol. 2006 Aug; 13(8):951-62.
Score: 0.013
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Evaluation of automated lung nodule detection on low-dose computed tomography scans from a lung cancer screening program(1). Acad Radiol. 2005 Mar; 12(3):337-46.
Score: 0.012
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Application of an artificial neural network to high-resolution CT: usefulness in differential diagnosis of diffuse lung disease. AJR Am J Roentgenol. 2004 Aug; 183(2):297-305.
Score: 0.011
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Potential usefulness of an artificial neural network for differential diagnosis of interstitial lung diseases: pilot study. Radiology. 1990 Dec; 177(3):857-60.
Score: 0.004
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Computer-aided diagnosis in chest radiology. J Thorac Imaging. 1990 Jan; 5(1):67-76.
Score: 0.004