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This paper develops a novel two-parameter unit probability model which is the generalized form Kumaraswami distribution that exhibits greater flexibility compared to well-known existing distributions, attributed to its distinct hazard and density function shapes. Extensive analysis has been conducted to explore numerous statistical features of the specified distribution, specifically moments, and order statistics providing explicit expressions for these measures. The maximum likelihood estimation is employed to estimate the model parameters and a numerical simulation analysis confirms the consistency of this estimation approach. Furthermore, the applicability of the specified model is demonstrated by considering four real data sets, showcasing its effectiveness in capturing the characteristics of real life data. The proposed model shows promise as a versatile tool for analyzing diverse data sets in a wide range of fields.

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Introduction: In the evolving healthcare landscape, we aim to integrate hyperspectral imaging into Hybrid Health Care Units to advance the diagnosis of medical diseases through the effective fusion of cutting-edge technology. The scarcity of medical hyperspectral data limits the use of hyperspectral imaging in disease classification. Methods: Our study innovatively integrates hyperspectral imaging to characterize tumor tissues across diverse body locations, employing the Sharpened Cosine Similarity framework for tumor classification and subsequent healthcare recommendation. The efficiency of the proposed model is evaluated using Cohen's kappa, overall accuracy, and f1-score metrics. Results: The proposed model demonstrates remarkable efficiency, with kappa of 91.76%, an overall accuracy of 95.60%, and an f1-score of 96%. These metrics indicate superior performance of our proposed model over existing state-of-the-art methods, even in limited training data. Conclusion: This study marks a milestone in hybrid healthcare informatics, improving personalized care and advancing disease classification and recommendations.

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This research explores the use of gated recurrent units (GRUs) for automated brain tumor detection using MRI data. The GRU model captures sequential patterns and considers spatial information within individual MRI images and the temporal evolution of lesion characteristics. The proposed approach improves the accuracy of tumor detection using MRI images. The model's performance is benchmarked against conventional CNNs and other recurrent architectures. The research addresses interpretability concerns by employing attention mechanisms that highlight salient features contributing to the model's decisions. The proposed model attention-gated recurrent units (A-GRU) results show promising results, indicating that the proposed model surpasses the state-of-the-art models in terms of accuracy and obtained 99.32% accuracy. Due to the high predictive capability of the proposed model, we recommend it for the effective diagnosis of Brain tumors in the E-healthcare system.

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BACKGROUND: Carpel tunnel syndrome is a common compression neuropathy of the median nerve causing pain, numbness and functional dysfunction of the hand. Among the available treatments, surgical release of the nerve is the most effective and acceptable treatment option. The aim of this study was to see the outcomes of surgical release of carpel tunnel using open technique. METHODS: This descriptive case series was conducted at the Department of neurosurgery, Ayub Teaching Hospital Abbottabad from April 2013 to March 2014. One hundred consecutive patients with carpel tunnel syndrome were included who underwent open carpel tunnel release surgery. They were followed up at 1, 3 and 6 months. Residual pain, numbness and functional improvement of the hand were the main outcome measures. RESULTS: Out of 100 patients, 19 were males. The age ranged from 32 to 50 years with a mean of 39.29±3.99 years. The duration of symptoms was from 5 to 24 months. In the entire series patient functional outcome and satisfaction was 82% at 1 month, 94% at 3 months and 97% at 6 months. 18% patient had residual pain at 1 month post-operative follow-up, 6% at 3 months and 3% at 6 month follow-up. CONCLUSION: Open carpel tunnel release surgery is an effective procedure for compression neuropathy of the median nerve. It should be offered to all patients with moderate to severe pain and functional disability related to carpel tunnel syndrome.

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BACKGROUND: Femoral shaft fracture is one of the common fractures seen in accident and emergency department of our hospital. Violent forces are required to break this and strongest of human bones. There are various treatment modalities for femoral shaft fractures in adults like traction, brace, platting, intramedullary nail (IMN), external fixators and inter locking nails. The study was done with an objective to evaluate the results of closed reamed interlocking nail in fractures of shaft of femur. METHODS: A prospective study of 114 cases of femoral shaft fractures was carried out at orthopaedic unit of Ayub Teaching Hospital Abbottabad during 1 year. All these cases were treated with statically locked nails under spinal or general anaesthesia. These cases were followed up for up to one year and Results of the interlocking nail were observed in terms of union and complications. RESULTS: Out of 114 patients, 95 underwent union in 90-150 days with a mean of 110.68 days. Ten patients had dynamization within six weeks because of obvious fracture gap in radiograph. There were 3 patients who had non-union, and 6 patients had delayed union which was treated with dynamization. CONCLUSION: Close reamed interlocking intramedullary nail in femoral shaft fractures is the treatment of choice. Patient rehabilitation is early, hospitalization is short, and fracture healing response is good.

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