Publications by authors named "Sp Praveen"

Introduction: Global Cardiovascular disease (CVD) is still one of the leading causes of death and requires the enhancement of diagnostic methods for the effective detection of early signs and prediction of the disease outcomes. The current diagnostic tools are cumbersome and imprecise especially with complex diseases, thus emphasizing the incorporation of new machine learning applications in differential diagnosis.

Methods: This paper presents a new machine learning approach that uses MICE for mitigating missing data, the IQR for handling outliers and SMOTE to address first imbalance distance.

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Heart strokes are a significant global health concern, profoundly affecting the wellbeing of the population. Many research endeavors have focused on developing predictive models for heart strokes using ML and DL techniques. Nevertheless, prior studies have often failed to bridge the gap between complex ML models and their interpretability in clinical contexts, leaving healthcare professionals hesitant to embrace them for critical decision-making.

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Article Synopsis
  • The text discusses the advancements in genomic technology and artificial intelligence for diagnosing and treating diseases, especially focusing on type 2 diabetes.
  • It highlights how machine learning, particularly Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRU), enhances the analysis of genetic data to predict illnesses.
  • The proposed model demonstrates promising accuracy in predicting diabetes and can be utilized in real-world applications, including an end-user Android app for collecting and evaluating risk factors securely.
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Carcinoma is a primary source of morbidity in women globally, with metastatic disease accounting for most deaths. Its early discovery and diagnosis may significantly increase the odds of survival. Breast cancer imaging is critical for early identification, clinical staging, management choices, and treatment planning.

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Chronic suppurative osteomyelitis (CSO) of the maxillofacial region is primarily caused by infections of odontogenic microorganisms. It may also arise as a complication of dental extractions, maxillofacial trauma, inadequate treatment of a fracture and irradiation to the mandible. This condition is characterized by areas of devitalized bone (sequestra) which serves as a nidus for recurrent episodes of infection.

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