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Data-driven analysis of climate impact on tomato and apple prices using machine learning.
Heliyon
January 2025
Department of Horticulture, Kongju National University, Yesan, 32439, Republic of Korea.
Machine learning has been used in various areas, but there are few studies on price prediction for agricultural products. Here, a machine learning technique for the price prediction of tomato and apple fruits was attempted based on environment and price data for 12 years. The goal of this study is to discover 1) how much can we accurately predict the product prices with the environmental factors and 2) how much each environmental factor affects to the product prices.
View Article and Find Full Text PDFA machine learning model to predict neurological deterioration after mild traumatic brain injury in older adults.
Front Neurol
January 2025
Department of Neurosurgery, Tokyo Medical and Dental University, Bunkyo-ku, Japan.
Objective: Neurological deterioration after mild traumatic brain injury (TBI) has been recognized as a poor prognostic factor. Early detection of neurological deterioration would allow appropriate monitoring and timely therapeutic interventions to improve patient outcomes. In this study, we developed a machine learning model to predict the occurrence of neurological deterioration after mild TBI using information obtained on admission.
View Article and Find Full Text PDFPrediction of Prostate Cancer From Routine Laboratory Markers With Automated Machine Learning.
J Clin Lab Anal
January 2025
Department of Medical Biochemistry, University of Health Sciences, Bursa Yuksek Ihtisas Training and Research Hospital, Bursa, Turkey.
Background: In this study, we attempted to select the optimum cases for a prostate biopsy based on routine laboratory test results in addition to prostate-specific antigen (PSA) blood test using H2O automated machine learning (AutoML) software, which includes many common machine learning algorithms.
Methods: The study included 737 patients (46-88 years old). Routine laboratory measurements were used to train machine learning models using H2O AutoML.
The Interplay between Metabolic Reprogramming, Mitochondrial Impairment, and Steroid Response in Proliferative Vitreoretinopathy.
Free Radic Biol Med
January 2025
Tianjin Key Laboratory of Retinal Functions and Diseases, Tianjin Branch of National Clinical Research Center for Ocular Disease, Eye Institute and School of Optometry, Tianjin Medical University Eye Hospital, Tianjin, P. R. China, No.251 Fu Kang Road, Nankai District, Tianjin 300384, P. R. China. Electronic address:
Proliferative vitreoretinopathy (PVR) is a major cause of rhegmatogenous retinal detachment repair failure. Despite many attempts to find therapeutics for PVR, no pharmacotherapy has been proven effective. Steroids, as the epitome, show uncertain clinical effectiveness, which lacks an explanation and hints at unappreciated mechanisms of PVR.
View Article and Find Full Text PDFErring on the side of caution: Two failures to replicate the derring effect.
J Exp Psychol Gen
January 2025
Centre for Perception and Cognition, School of Psychology, University of Southampton.
It has been claimed that deliberately making errors while studying, even when the correct answers are provided, can enhance memory for the correct answers, a phenomenon termed the derring effect. Such deliberate erring has been shown to outperform other learning techniques, including copying and underlining, elaborative studying with concept mapping, and synonym generation. To date, however, the derring effect has only been demonstrated by a single group of researchers and in a single population of participants.
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