The Role of Muscle Thickness and Echogenicity in the Diagnosis of Diabetic Peripheral Neuropathy

Kadhim, Zahid M.; Alkhafaji, Meqat M.

doi:10.14704/nq.2021.19.8.nq21121

Cited by 3 publications

(3 citation statements)

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“…As mentioned by Resmini (2019) if the teacher wants to discuss a topic with the students, they can use first language in order to help the students struggle with English. In contrast to what has mentioned above, Kadhim et al, (2022) argued that the use of the first language in foreign language learning is currently considered taboo, because many educational institutions are trying to prohibit the use of the first language in foreign language classes. The use of L1 in ELL have many benefits, for example: reducing barriers to learning and increasing self-confidence in the learning process is one of the benefits of using L1, so that students can understand the target language being taught (Liando & Tatipang, 2022).…”

Section: Introductionmentioning

confidence: 79%

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First Language Interfere in EFL Classes: Revealing Students’ Perspectives and Teachers’ Reasons in ELL

Liando,

Tatipang,

Wuntu

2023

REiLA Journal

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Multilingualism is a common phenomenon among Indonesian students who are proficient in both national and local languages. However, the use of the first language (L1) in English as a Foreign Language (EFL) classrooms has been a subject of ongoing debate. This study explores the use of the first language (L1) in English as a Foreign Language (EFL) classrooms by investigating the perspectives of Indonesian students and teachers’ reasons. The study used a qualitative approach with a in-depth semi-structured interviews conducted with teachers, and questionnaire for the students, convenience sampling was used to select 105 participants from grade 12 of IPA, IPS, and Bahasa. Results showed that the majority of students had a positive perspective on the use of L1 by their English teachers during lessons. However, there was no significant difference in the students' perspectives based on gender and major classes. Teachers' reasons for using L1 included bridging students' knowledge, motivating students, and creating an active learning atmosphere. However, the overuse of L1 was found to be a potential problem, as it could lead to a lack of mastery of the target language. The findings suggest that the use of L1 in EFL classrooms can be beneficial but should be used in moderation to avoid students becoming too reliant on it. Teachers should use L1 as a means to facilitate learning, not as a substitute for the target language. This study provides important insights into the use of L1 in EFL classrooms from the perspectives of both students and teachers. These findings have important implications for language teaching practices and policies, not only in Indonesia but also in other multilingual contexts worldwide. Further research is needed to explore the long-term effects of L1 use on language acquisition and to develop effective strategies to minimize its negative impact.

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Section: Introductionmentioning

confidence: 79%

“…As Kadhim et al, (2022) claimed that the mother tongue has a significant role in improving the students' English ability. In addition, the mother tongue provides a good role to clarify instruction, pronunciation and express their frustration or difficulties (Khasawneh, 2021).…”

Section: The Use Of First Language During English Lessonmentioning

confidence: 99%

First Language Interfere in EFL Classes: Revealing Students’ Perspectives and Teachers’ Reasons in ELL

Liando,

Tatipang,

Wuntu

2023

REiLA Journal

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“…A survey on the previous work carried out to find the best tool that has been used for the diagnosis of DPN and investigates the new techniques that can be combined on an integration system for the precise diagnosis system: Zahid et al in 2021 [11] showed that the muscle ultrasound as a valuable and complementary tool for the diagnosis of DPN, where the thickness and the echogenicity of lower limbs muscle ultrasound in patients with DPN and casecontrol study had been conducted alongside the NCS, physical examination and history characteristic of those groups. The outcome result was a statistically significant increase in the echogenicity and decrease in muscle thickness of tested patients compared with control group.…”

Section: Introductionmentioning

confidence: 99%

A complementary Diagnostic Tool for Diabetic Peripheral Neuropathy Through Muscle Ultrasound and Machine Learning Algorithms

Kamal,

Al-Timemy,

Kadhim

et al. 2024

NJES

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Diabetic peripheral neuropathy represents one of the common long-terms complications that effect about fifty percentage?of diabetes patients. The habitual diagnosis tool based on nerve conduction study that examine the nerve damage and classify the patient status into normal and diabetic peripheral neuropathy with degree of severity without considering the effect on skeletal muscle and take on patient data. A complementary diagnostic tool proposed, in this study integrates the patient’s data including body mass index, age and duration of diabetic, average blood glucose levels, nerve conduction study that involves amplitude and latency of peroneal and tibial nerves and muscle ultrasound alongside the machine learning algorithms to facilitate the clinicians for a precise diagnosis. A group of control and diabetic patients utilized to gather the data with calculating the muscle thickness and statistical properties from the gray-level ultrasound images of six skeletal muscles. Support vector machine, naïve bayes, ensemble of bagged tree and artificial neural network supervised machine learning algorithms categorize each class with a high classification accuracy, 98.1% for tibialis anterior with naïve bayes algorithm. The outcomes of this study show a promising complementary diagnostic tool that will help the clinicians to perform an exact diagnosis and disclose the side effect on both nerves and muscles of diabetic patients.

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Bag of Feature-Based Ensemble Subspace KNN Classifier in Muscle Ultrasound Diagnosis of Diabetic Peripheral Neuropathy

Al-Barazanchi,

Al-Timemy,

Kadhim

2024

MCA

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Muscle ultrasound quantification is a valuable complementary diagnostic tool for diabetic peripheral neuropathy (DPN), enhancing physicians’ diagnostic capabilities. Quantitative assessment is generally regarded as more reliable and sensitive than visual evaluation, which often necessitates specialized expertise. This work develops a computer-aided diagnostic (CAD) system based on muscle ultrasound that integrates the bag of features (BOF) and an ensemble subspace k-nearest neighbor (KNN) algorithm for DPN detection. The BOF creates a histogram of visual word occurrences to represent the muscle ultrasound images and trains an ensemble classifier through cross-validation, determining optimal parameters to improve classification accuracy for the ensemble diagnosis system. The dataset includes ultrasound images of six muscles from 53 subjects, consisting of 27 control and 26 patient cases. An empirical analysis was conducted for each binary classifier based on muscle type to select the best vocabulary tree properties or K values for BOF. The result indicates that ensemble subspace KNN classification, based on the bag of features, achieved an accuracy of 97.23%. CAD systems can effectively diagnose muscle pathology, thereby addressing limitations and identifying issues in individuals with diabetes. This research underscores muscle ultrasound as a promising diagnostic tool to aid physicians in making accurate diagnoses, streamlining workflow, and uncovering muscle-related complications in DPN patients.

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The Role of Muscle Thickness and Echogenicity in the Diagnosis of Diabetic Peripheral Neuropathy

Cited by 3 publications

References 0 publications

First Language Interfere in EFL Classes: Revealing Students’ Perspectives and Teachers’ Reasons in ELL

First Language Interfere in EFL Classes: Revealing Students’ Perspectives and Teachers’ Reasons in ELL

A complementary Diagnostic Tool for Diabetic Peripheral Neuropathy Through Muscle Ultrasound and Machine Learning Algorithms

Bag of Feature-Based Ensemble Subspace KNN Classifier in Muscle Ultrasound Diagnosis of Diabetic Peripheral Neuropathy

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