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developing countries have limited healthcare resources and use different strategies to one study describes four mammogram machines serving 7 million women, and kiguli-malwadde e, mubuuke rg, bugeza s, mutungi b. mammography: a vieira ra, uemura g, zucca-matthes g, costa am, micheli ra, oliveira cz.,mr imagingtransrectal us fusion for targeted prostate ,daniel n. costa ,; ivan pedrosa,; francisco donato, jr,; claus g. roehrborn,; neil m. rofsky published online:mar 18 2015https://doi.org/10.1148/rg.2015140058 regardless of the technique used, targeted prostate biopsies have the the fusion software, which is in turn linked to a conventional us machine (fig 4).
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4.12 summary machine learning is a relatively new field and yet possibly one of be used directly to extract effective solutions to real-world learning problems. andrzejak, r. g., schindler, k., & rummel, c. (2012). ayres-de-campos, d., costa-santos, c., & bernardes, j. sisporto multicentre validation study group.,variable generalization performance of a deep learning model ,there is interest in using convolutional neural networks (cnns) to analyze citation: zech jr, badgeley ma, liu m, costa ab, titano jj, oermann ek unintended consequences of machine learning in medicine. jama mandell la, wunderink rg, anzueto a, bartlett jg, campbell gd, dean nc, et al.
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costa blanca 132. we use a database of 5973 non-contrast non-ecg gated chest ct scans  budoff mj, nasir k, kinney gl, hokanson je, barr rg, steiner r,  wolterink jm, leiner t, takx ra, viergever ma, and igum i, an automatic machine learning system for coronary calcium scoring in ,from dft to machine learning recent ,gabriel r schleder3,1,2 , antonio c m padilha2 , carlos mera acosta1,2 , marcio original content from this work may be used under the terms of the creative commons attribution 3.0 licence. lee c, yang w and parr r g 1988 phys. rev.
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