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The rapid impact assessment matrix (RIAM) is a widely utilized tool for evaluating environmental impacts in municipal solid waste management. However, the traditional RIAM (T-RIAM) method includes ambiguities in its scoring classification, which can hinder decision-making accuracy. This study introduces a modified RIAM approach, enhancing classification precision by refining impact categories, making it particularly valuable for projects constrained by time and resources.

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Chondrosarcoma-like malignant giant cell tumor (GCT) of the rib is an extremely rare and aggressive tumor, particularly in adolescents. This case report describes a 19-year-old female presenting with a GCT of the rib with chondrosarcomatous differentiation, highlighting the challenges posed by its unusual location and pathological complexity. Multidisciplinary diagnostic approaches, including advanced imaging, immunohistochemistry (IHC), and pathology, were essential for confirming the diagnosis.

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Background: Postural Orthostatic Tachycardia Syndrome (POTS) is a complex form of dysautonomia that presents with abnormal autonomic reflexes upon standing, leading to symptoms such as lightheadedness, tachycardia, fatigue, and cognitive impairment. The COVID-19 pandemic has brought renewed attention to POTS due to its overlap with post-acute sequelae of COVID-19 (PASC). Studies have found that a substantial percentage of COVID-19 survivors exhibit symptoms resembling POTS, elevating POTS diagnoses to previously unseen levels.

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Radiomics-based Machine Learning Approach to Predict Chemotherapy Responses in Colorectal Liver Metastases.

J Anus Rectum Colon

January 2025

Department of Gastroenterological Surgery, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan.

Objectives: This study explored the clinical utility of CT radiomics-driven machine learning as a predictive marker for chemotherapy response in colorectal liver metastasis (CRLM) patients.

Methods: We included 150 CRLM patients who underwent first-line doublet chemotherapy, dividing them into a training cohort (n=112) and a test cohort (n=38). We manually delineated three-dimensional tumor volumes, selecting the largest liver metastasis for measurement, using pretreatment portal-phase CT images and extracted 107 radiomics features.

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CECT-Based Radiomic Nomogram of Different Machine Learning Models for Differentiating Malignant and Benign Solid-Containing Renal Masses.

J Multidiscip Healthc

January 2025

Department of Nuclear Medicine, The First People's Hospital of Yunnan Province, the Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan, 650032, People's Republic of China.

Objective: This study aimed to explore the value of a radiomic nomogram based on contrast-enhanced computed tomography (CECT) for differentiating benign and malignant solid-containing renal masses.

Materials And Methods: A total of 122 patients with pathologically confirmed benign (n=47) or malignant (n=75) solid-containing renal masses were enrolled in this study. Radiomic features were extracted from the arterial, venous and delayed phases and further analysed by dimensionality reduction and selection.

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