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Total 32 results found since Jan 2013.
Risk Factors of Hyperglycemia After Treatment With the AKT Inhibitor Ipatasertib in the Prostate Cancer Setting: A Machine Learning-Based Investigation
CONCLUSION: The findings support using patients' prediabetic status as a key factor for hyperglycemia monitoring and/or trial exclusion criteria. Additionally, the model and relationships between explanatory variables and HGLY ≥2 described herein can help identify patients at high risk for hyperglycemia and develop rational risk mitigation strategies.PMID:37116107 | DOI:10.1200/CCI.22.00168
Source: Clinical Prostate Cancer - April 28, 2023 Category: Cancer & Oncology Authors: Rashed Harun Rucha Sane Kenta Yoshida Dhruvitkumar S Sutaria Jin Y Jin James Lu Source Type: research
Hidden hydrogen: Earth may hold vast stores of a renewable, carbon-free fuel
IN THE SHADE
of a mango tree, Mamadou Ngulo Konaré recounted the legendary event of his childhood. In 1987, well diggers had come to his village of Bourakébougou, Mali, to drill for water, but had given up on one dry borehole at a depth of 108 meters. “Meanwhile, wind was coming out of the hole,” Konaré told Denis Brière, a petrophysicist and vice president at Chapman Petroleum Engineering, in 2012. When one driller peered into the hole while smoking a cigarette, the wind exploded in his face.
“He didn’t die, but he was burned,” Konaré continued. “And now we had a huge fire. The color of the fire...
Source: ScienceNOW - February 16, 2023 Category: Science Source Type: news
Efficacy of GIS-based AHP and data-driven intelligent machine learning algorithms for irrigation water quality prediction in an agricultural-mine district within the Lower Benue Trough, Nigeria
This study showed that the integration of GIS-AHP and machine learning can serve as efficient and rapid decision-making tools in irrigation water quality monitoring and prediction.PMID:36723836 | DOI:10.1007/s11356-023-25291-3
Source: Environmental Science and Pollution Research International - February 1, 2023 Category: Environmental Health Authors: Michael E Omeka Ogbonnaya Igwe Obialo S Onwuka Ogechukwu M Nwodo Samuel I Ugar Peter A Undiandeye Ifeanyi E Anyanwu Source Type: research
Prediction of nano, fine, and medium colloidal phosphorus in agricultural soils with machine learning
Environ Res. 2023 Jan 4;220:115222. doi: 10.1016/j.envres.2023.115222. Online ahead of print.ABSTRACTSoil colloids have been shown to play a critical role in soil phosphorus (P) mobility and transport. However, identifying the potential mechanisms behind colloidal P (Pcoll) release and the key influencing factors remains a blind spot. Herein, a machine learning approach (random forest (RF) coupled with partial dependence plot analyses) was applied to determine the effects of different soil physicochemical parameters on Pcoll content in three colloidal subfractions (i.e., nano- (NC): 1-20 nm, fine- (FC): 20-220 nm and mediu...
Source: Environmental Research - January 7, 2023 Category: Environmental Health Authors: Kamel Mohamed Eltohamy Sangar Khan Shuang He Jianye Li Chunlong Liu Xinqiang Liang Source Type: research
Importance of hydration in cardiovascular health and cognitive function
Nutr Hosp. 2022 Jul 28. doi: 10.20960/nh.04304. Online ahead of print.ABSTRACTWater is an essential nutrient for health. Inadequate water intake induces states of dehydration and hypovolemia,causing an increase in plasma osmolality proportional to the decrease in body water. Restricting water intake can have harmful effects on cardiovascular health by affecting endothelial function and increasing the viscosity of blood, haematocrit and fibrinogen. Adequate hydration is associated with lower risk of deadly coronary heart disease. Obesity and diabetes are risk factors for cardiovascular disease. Hypohydration is linked to we...
Source: Nutricion Hospitalaria - August 30, 2022 Category: Nutrition Authors: Rosa Mar ía Martínez García Ana Isabel Jim énez Ortega Ana Mar ía Lorenzo-Mora Laura Mar ía Bermejo Source Type: research
Prediction of irrigation groundwater quality parameters using ANN, LSTM, and MLR models
Environ Sci Pollut Res Int. 2021 Nov 8. doi: 10.1007/s11356-021-17084-3. Online ahead of print.ABSTRACTForecasting the irrigation groundwater parameters helps plan irrigation water and crop, and it is commonly expensive because it needs various parameters, mainly in developing nations. Therefore, the present research's core objective is to create accurate and reliable machine learning models for irrigation parameters. To accomplish this determination, three machine learning (ML) models, viz. long short-term memory (LSTM), multi-linear regression (MLR), and artificial neural network (ANN), have been trained. It is validated...
Source: Environmental Science and Pollution Research International - November 8, 2021 Category: Environmental Health Authors: Saber Kouadri Chaitanya B Pande Balamurugan Panneerselvam Kanak N Moharir Ahmed Elbeltagi Source Type: research
Some Patients Are Reporting Long COVID Recoveries —But Experts Still Don’t Fully Understand Why
A few months ago, Lana Lynch had resigned herself to never getting better. Months after testing positive for COVID-19, she still felt fatigued, still got daily headaches, still had to carefully regulate how much she exerted herself each day. She was coming to terms with her new normal—until she didn’t have to.
After receiving her second dose of the Pfizer-BioNTech COVID-19 vaccine in May, Lynch, a 32-year-old from Texas, noticed that she wasn’t quite so tired anymore. She could get through a yoga class without hitting a wall. “I felt like I had some energy,” she says, “but I didn’t...
Source: TIME: Health - June 9, 2021 Category: Consumer Health News Authors: Jamie Ducharme Tags: Uncategorized COVID-19 Source Type: news
Prediction of water quality parameters using machine learning models: a case study of the Karun River, Iran
Environ Sci Pollut Res Int. 2021 Jun 3. doi: 10.1007/s11356-021-14560-8. Online ahead of print.ABSTRACTAccurate water quality predicting has an essential role in improving water management and pollution control. The machine learning models have been successfully implemented for modelling total dissolved solids (TDS), sodium absorption ratio (SAR) and total hardness (TH) content in aquatic ecosystems with insufficient data. However, due to multiple pollution sources and complex behaviours of pollutants, these models' effect in predicting TDS, SAR, and TH levels in the Karun River system is still unclear. Given this problem,...
Source: Environmental Science and Pollution Research International - June 3, 2021 Category: Environmental Health Authors: Atefeh Nouraki Mohammad Alavi Mona Golabi Mohammad Albaji Source Type: research
