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1.
Eur Spine J ; 31(8): 2022-2030, 2022 08.
Article in English | MEDLINE | ID: mdl-35089420

ABSTRACT

PURPOSE: To improve the performance of less experienced clinicians in the diagnosis of benign and malignant spinal fracture on MRI, we applied the ResNet50 algorithm to develop a decision support system. METHODS: A total of 190 patients, 50 with malignant and 140 with benign fractures, were studied. The visual diagnosis was made by one senior MSK radiologist, one fourth-year resident, and one first-year resident. The MSK radiologist also gave the binary score for 15 qualitative imaging features. Deep learning was implemented using ResNet50, using one abnormal spinal segment selected from each patient as input. The T1W and T2W images of the lesion slice and its two neighboring slices were considered. The diagnostic performance was evaluated using tenfold cross-validation. RESULTS: The overall reading accuracy was 98, 96, and 66% for the senior MSK radiologist, fourth-year resident, and first-year resident, respectively. Of the 15 imaging features, 10 showed a significant difference between benign and malignant groups with p < = 0.001. The accuracy achieved by using the ResNet50 deep learning model for the identified abnormal vertebral segment was 92%. Compared to the first-year resident's reading, the model improved the sensitivity from 78 to 94% (p < 0.001) and the specificity from 61 to 91% (p < 0.001). CONCLUSION: Our deep learning-based model may provide information to assist less experienced clinicians in the diagnosis of spinal fractures on MRI. Other findings away from the vertebral body need to be considered to improve the model, and further investigation is required to generalize our findings to real-world settings.


Subject(s)
Deep Learning , Spinal Fractures , Spinal Neoplasms , Diagnosis, Differential , Humans , Magnetic Resonance Imaging/methods , Retrospective Studies , Spinal Fractures/diagnosis , Spinal Neoplasms/pathology
2.
Percept Mot Skills ; 120(2): 576-90, 2015 Apr.
Article in English | MEDLINE | ID: mdl-25914939

ABSTRACT

This study examined the effects of audio-visual aids on anxiety, comprehension test scores, and retention in reading and listening to short stories in English as a Foreign Language (EFL) classrooms. Reading and listening tests, general and test anxiety, and retention were measured in English-major college students in an experimental group with audio-visual aids (n=83) and a control group without audio-visual aids (n=94) with similar general English proficiency. Lower reading test anxiety, unchanged reading comprehension scores, and better reading short-term and long-term retention after four weeks were evident in the audiovisual group relative to the control group. In addition, lower listening test anxiety, higher listening comprehension scores, and unchanged short-term and long-term retention were found in the audiovisual group relative to the control group after the intervention. Audio-visual aids may help to reduce EFL learners' listening test anxiety and enhance their listening comprehension scores without facilitating retention of such materials. Although audio-visual aids did not increase reading comprehension scores, they helped reduce EFL learners' reading test anxiety and facilitated retention of reading materials.


Subject(s)
Anxiety/psychology , Audiovisual Aids , Comprehension/physiology , Multilingualism , Reading , Retention, Psychology/physiology , Speech Perception/physiology , Adult , Female , Humans , Learning/physiology , Male , Young Adult
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