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PURPOSE: This study investigates the potential of machine learning (ML) algorithms in improving sepsis diagnosis and prediction, focusing on their relevance in healthcare decision-making. The primary objective is to contribute to healthcare decision-making by evaluating the performance of various supervised and unsupervised models. MATERIALS AND METHODS: Through an extensive literature review, optimal ML models used in sepsis research were identified. Diverse datasets from relevant sources were employed, and rigorous evaluation metrics, including accuracy, specificity, and sensitivity, were applied. Innovative techniques were introduced, such as a Stacked Blended Ensemble Model and Skopt Optimization with Blended Ensemble, incorporating Bayesian optimization for hyperparameter tuning. RESULTS: ML algorithms demonstrate efficacy in sepsis diagnosis, presenting an improved balance between specificity and sensitivity, critical for effective clinical decision-making. Classifier ensemble models show enhanced accuracy and efficiency, with novel optimization techniques contributing to improved adaptability. CONCLUSION: The study emphasizes the potential benefits of ML algorithms in sepsis management, advocating for ongoing research to optimize performance and ensure ethical utilization in healthcare decision-making. Ethical considerations, interpretability, and transparency are crucial factors in implementing these algorithms in clinical practice.
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Introduction Myofascial pain is defined as pain arising primarily in muscles and associated with multiple trigger points. Among the non-pharmacological methods, trigger point injection and electrotherapy are effective methods to treat myofascial pain syndrome. This study compares the effectiveness of dry needling (DN) and transcutaneous electrical nerve stimulation (TENS) in reducing cervical pain intensity and improving cervical range of motion in patients with neck pain due to myofascial trigger points. Methods Fifty patients were enrolled and randomized into two groups. Patients in group A received dry needling, and those in group B received TENS. Patients were evaluated using the Visual Analog Scale (VAS), Neck Disability Index (NDI), and Cervical Range of Motion (CROM) before the treatment and on days 14 and 28 after the treatment. The unpaired t-test was used to evaluate quantitative data, except for VAS, where the Mann-Whitney U test was used. All quantitative variables had a normal distribution with a standard deviation except for pain intensity (VAS), which deviated from the normal distribution. The significance level was set at a P-value=0.05. Results Both DN and TENS groups showed significant improvement in VAS, NDI, and CROM between days 0 and 28 (p=<0.001). The DN group showed greater improvements in pain intensity from day 0 to day 28 (p =<0.001). Between days 0 and 28, there was no discernible difference in NDI changes between the groups (p = 0.157 and p = 0.799, respectively). Mixed results were obtained for CROM, with significant improvement of cervical flexion in the dry needling group (p=<0.008) and significant improvement of cervical rotation to the painful side in the TENS group (<0.001). Conclusion Both dry needling and TENS are effective in reducing pain and improving NDI and CROM in patients with neck pain due to myofascial trigger points. However, as dry needling is more effective in pain reduction, a single session of dry needling is more beneficial and cost-effective as compared to multiple sessions of TENS.
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Dentigerous cyst is reported to be one of the most common odontogenic cysts of the jaws.(12) The most commonly involved teeth are mandibular third molars, maxillary canines, maxillary third molars and rarely maxillary anteriors.(23) This case report is about the management of a dentigerous cyst associated with a mandibular second molar (37) in a 9-year-old girl by a conservative treatment plan of marsupialization of the cyst. A 2-year postsurgical review reveals complete disappearance of the cystic lesion and normal alignment of 37 and 38.
