Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...
Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...
Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.
Sensors, computer vision models, and artificial intelligence have combined to help CEAT Tyres’ Chennai factory reduce defects, waste and energy use, a.
A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
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Study shows sharp oasis decline in southeastern Morocco’s Ternata over the past 40 years
A group of eight researchers has pointed to a steady decline in the Ternata Oasis, southeastern Morocco, over the past 40 ...
Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
Researchers used 16S rRNA sequencing and machine learning to identify gut microbiome patterns associated with insulin resistance severity in people with type 2 diabetes. XGBoost models showed that ...
By now, ChatGPT, Claude, and other large language models have accumulated so much human knowledge that they're far from simple answer-generators; they can also express abstract concepts, such as ...
As Raipur expands, the Kharun River Basin faces intensifying floods and sediment loads. Explore how climate change and land-use shifts are erasing the predictability of India’s monsoon heartland.
In the first instalment of LCGC International's interview series exploring how artificial intelligence (AI)/machine learning ...
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