Publications by authors named "A Sachin Aslam"

The aim of the present study was to investigate the potential of human plasma derived exosomes for the delivery of hydroxyurea to enhance its therapeutic efficacy in breast cancer. Plasma derived exosomes were isolated using differential centrifugation along with ultrafiltration method. Hydroxyurea was encapsulated in exosomes using a freeze-thaw method.

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The rapid integration of artificial intelligence into healthcare has introduced transformative possibilities and challenges. The current narrative review was planned to explore diverse applications of Chat Generative Pre-Trained Transformer (ChatGPT) across medical domains, ranging from dietary planning and disease management to medical education and clinical decision support. A comprehensive analysis of ChatGPT's healthcare applications was conducted between July and September 2023, reviewing literature from prominent medical journals and databases, including PubMed, Embase, Cochrane library and the Cumulated Index in Nursing and Allied Health Literature.

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Objective: To assess the efficacy of renal score grading in guiding therapy decisions, predicting perioperative outcomes, and characterising tumours following partial nephrectomy.

Methods: The retrospective, single-centre study was conducted at the University College Hospital Galway, Ireland, and comprised data from January 11, 2012, to June 17, 2016, of all patients aged >18 years who underwent partial nephrectomy as part of treatment for kidney cancer. Data was analysed using SPSS 20.

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Chronic myeloid leukemia (CML) is a myeloproliferative disorder that commonly manifests in chronic, accelerated, or blast phase. Typically observed in individuals aged 60-65 years, CML is infrequently diagnosed in adolescents. The usual presentation in late adulthood involves nonspecific symptoms such as fever, fatigue, and weight loss, with rare reports of initial neurological involvement.

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Background: Chronic liver disease (CLD) is a substantial cause of morbidity and mortality worldwide. Liver stiffness, as measured by MR elastography (MRE), is well-accepted as a surrogate marker of liver fibrosis.

Purpose: To develop and validate deep learning (DL) models for predicting MRE-derived liver stiffness using routine clinical non-contrast abdominal T1-weighted (T1w) and T2-weighted (T2w) data from multiple institutions/system manufacturers in pediatric and adult patients.

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