"can't classify 0 points instead of 2 points"
"Artificial Intelligence Thyroid Imaging Reporting and Data System (AI TI-RADS) is a data-driven analysis and revision of the 2017 ACR TI-RADS 1. Published in May 2019 2, this had the intention of simplifying categorisation and improving specificity while maintaining high sensitivity. This system used a training set of 1325 nodules with known cytology and a genetic learning algorithm to optimise the current lexicon and scoring structure. This system was then applied by expert and nonexpert radiologists and compared with known ACR TI-RADS categories."
"Artificial Intelligence Thyroid Imaging Reporting and Data System (AI TI-RADS) is a data-driven analysis and revision of the 2017 ACR TI-RADS 1. Published in May 2019 2, this had the intention of simplifying categorisation and improving specificity while maintaining high sensitivity. This system used a training set of 1325 nodules with known cytology and a genetic learning algorithm to optimise the current lexicon and scoring structure. This system was then applied by expert and nonexpert radiologists and compared with known ACR TI-RADS categories."
"Artificial Intelligence Thyroid Imaging Reporting and Data System (AI TI-RADS) is a data-driven analysis and revision of the 2017 ACR TI-RADS 1. Published in May 2019 2, this had the intention of simplifying categorisation and improving specificity while maintaining high sensitivity. This system used a training set of 1325 nodules with known cytology and a genetic learning algorithm to optimise the current lexicon and scoring structure. This system was then applied by expert and nonexpert radiologists and compared with known ACR TI-RADS categories."
"Artificial Intelligence Thyroid Imaging Reporting and Data System (AI TI-RADS) is a data-driven analysis and revision of the 2017 ACR TI-RADS 1. Published in May 2019 2, this had the intention of simplifying categorisation and improving specificity while maintaining high sensitivity. This system used a training set of 1325 nodules with known cytology and a genetic learning algorithm to optimise the current lexicon and scoring structure. This system was then applied by expert and nonexpert radiologists and compared with known ACR TI-RADS categories."
"Artificial Intelligence Thyroid Imaging Reporting and Data System (AI TI-RADS) is a data-driven analysis and revision of the 2017 ACR TI-RADS 1. Published in May 2019 2, this had the intention of simplifying categorisation and improving specificity while maintaining high sensitivity. This system used a training set of 1325 nodules with known cytology and a genetic learning algorithm to optimise the current lexicon and scoring structure. This system was then applied by expert and nonexpert radiologists and compared with known ACR TI-RADS categories."
"Artificial Intelligence Thyroid Imaging Reporting and Data System (AI TI-RADS) is a data-driven analysis and revision of the 2017 ACR TI-RADS 1. Published in May 2019 2, this had the intention of simplifying categorisation and improving specificity while maintaining high sensitivity. This system used a training set of 1325 nodules with known cytology and a genetic learning algorithm to optimise the current lexicon and scoring structure. This system was then applied by expert and nonexpert radiologists and compared with known ACR TI-RADS categories."
"Changes to ACR TI-RADS"
"Changes to ACR TI-RADS"
"cystic and spongiform nodules again receive 0 points, but AI TI-RADS found this sufficient to assign benignity regardless of findings in any of the other categories"
"cystic and spongiform nodules again receive 0 points, but AI TI-RADS found this sufficient to assign benignity regardless of findings in any of the other categories"
"The point level for each TR category and recommendation for FNA by size remained the same."
"The point level for each TR category and recommendation for FNA by size remained the same."
"Outcome comparison with ACR TI-RADS"
"Outcome comparison with ACR TI-RADS"
"Tested against 100 nodules, sensitivity was identical between AI and ACR TI-RADS (93%). Specificity was increased for AI TI-RADS at 65% compared with 47% with a single expert reader, and also an increase of 55% from 47% in a non-expert reader group."
"Tested against 100 nodules, sensitivity was identical between AI and ACR TI-RADS (93%). Specificity was increased for AI TI-RADS at 65% compared with 47% with a single expert reader, and also an increase of 55% from 47% in a non-expert reader group."
"Tested against 100 nodules, sensitivity was identical between AI and ACR TI-RADS (93%). Specificity was increased for AI TI-RADS at 65% compared with 47% with a single expert reader, and also an increase of 55% from 47% in a non-expert reader group."
"Tested against 100 nodules, sensitivity was identical between AI and ACR TI-RADS (93%). Specificity was increased for AI TI-RADS at 65% compared with 47% with a single expert reader, and also an increase of 55% from 47% in a non-expert reader group."
"Tested against 100 nodules, sensitivity was identical between AI and ACR TI-RADS (93%). Specificity was increased for AI TI-RADS at 65% compared with 47% with a single expert reader, and also an increase of 55% from 47% in a non-expert reader group."
"43 nodules were down categorised, with 15 nodules not meeting requirement for FNA (all of which were benign). No extra malignancies were missed using the AI TI-RADS scoring algorithm."
"43 nodules were down categorised, with 15 nodules not meeting requirement for FNA (all of which were benign). No extra malignancies were missed using the AI TI-RADS scoring algorithm."
"43 nodules were down categorised, with 15 nodules not meeting requirement for FNA (all of which were benign). No extra malignancies were missed using the AI TI-RADS scoring algorithm."
"ACR TI-RADS"
"ACR TI-RADS"
"RADS (Reporting and Data Systems)"
Expected headings
"Changes to ACR TI-RADS"
"Outcome comparison with ACR TI-RADS"