METHODS: A comparative cross sectional study design involving 379 pregnant women was used to assess the prevalence of anaemia and low intake of dietary nutrients in pregnant women living in rural and urban areas in the Ashanti region of Ghana. Anaemia status and mid upper arm circumference (MUAC) were used as proxy for maternal nutritional status. Haemoglobin measurements were used to determine anaemia prevalence and the dietary diversity of the women were determined with a 24-hour dietary recall and a food frequency questionnaire.
RESULTS: Overall, anaemia was present in 56.5% of the study population. Anaemia prevalence was higher among rural residents than urban dwellers. Majority of the respondents had inadequate intakes of iron, zinc, folate, calcium and vitamin A. The mean dietary diversity score (DDS) of the study population from the first 24-hour recall was 3.81 ± 0.7. Of the 379 women, 28.8% met the minimum dietary diversity for women (MDD-W). The independent predictors of haemoglobin concentration were, gestational age, maternal age and dietary diversity score. Such that respondents with low DDS were more likely to be anaemic than those with high DDS (OR = 1.795, p = 0.022, 95% CI: 1.086 to 2.967).
CONCLUSIONS: A large percentage of pregnant women still have insufficient dietary intakes of essential nutrients required to support the nutritional demands during pregnancy. Particularly, pregnant women resident in rural areas require interventions such as nutrition education on the selection and preparation of diversified meals to mitigate the effects of undernutrition.
METHODS: This study reviews the use of DL for Anterior Cruciate Ligament (ACL) tear diagnosis. A comprehensive search was performed in PubMed, Embase, and Web of Science databases from 2018 to 2024. The included study criteria used MRI images to evaluate ACL tears, and the diagnosis of ACL tears was performed using the DL model. We summarized the paper by reporting their model accuracy, model comparison with arthroscopy, and explainable.
RESULTS: AI implementation in tabular format; we conclude that many medical professionals believe that arthroscopic diagnosis is the most reliable method for diagnosing ACL tears. However, due to its intrusive treatment, CAD is projected to be able to produce similar outcomes from MRI scan results. To gain the trust of physicians and meet the demand for reliable knee injury detection systems, an algorithm for CAD should also meet several criteria, such as being transparent, interpretable, explainable, and easy to use. Therefore, future works should consider creating an Explainable DL model for ACL tear diagnosis. It is also essential to evaluate the performance of this Explainable DL model compared to the gold standard of arthroscopy diagnosis.
CONCLUSION: There are issues regarding the need for Explainable DL in CAD to increase confidence in its result while also highlighting the importance of the involvement of medical practitioners in system design. There is no funding for this work.