AIMC Topic: Machine Learning

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Biological age threshold is associated with symptomatic knee osteoarthritis risk in chinese adults: Insights from machine learning analysis of a national cohort.

PloS one
BACKGROUND: Symptomatic knee osteoarthritis (KOA) imposes a substantial global health and economic burden. Although chronological age (CA) is a key risk factor, it poorly reflects interindividual aging heterogeneity. Biological age (BA), which is qua...

Combining crystal engineering and surface engineering to estimate the structure -functions relationship of Tafamidis solid state forms with the aid of machine learning.

International journal of pharmaceutics
The mutual benefits of surface engineering and crystal engineering led to the discovery of a pharmaceutical cocrystal with balanced biopharmaceutical properties. The surface engineering of a pharmaceutical API (Active Pharmaceutical Ingredient), name...

Exploring shared diagnostic genes and molecular mechanisms in multiple sclerosis and psoriasis through bioinformatics analysis and machine learning.

Biochemical and biophysical research communications
BACKGROUND: Multiple sclerosis (MS) and psoriasis are both immune-mediated inflammatory diseases. Previous studies have reported comorbidity between MS and psoriasis, but the underlying mechanisms remain unclear. This study aims to elucidate the shar...

Machine Learning-Driven Extracellular Vesicles Peptidomics Powers Precision Classification of Endometrial Cancer.

Analytical chemistry
Endometrial cancer (EC) molecular subtyping is critical for prognosis and treatment but remains hindered by reliance on invasive tissue biopsies and time-consuming genomic sequencing. Here, we present a minimally invasive approach integrating MALDI-T...

Quantifying the contributions of climate change and adaptation to mortality from unprecedented extreme heat events.

Proceedings of the National Academy of Sciences of the United States of America
Understanding the mortality effects of the most extreme heat events is central to climate change risk analysis and adaptation decision-making. Accurate representation of these impacts requires accounting for the effects of prolonged sequences of hot ...

Association of albumin-bilirubin grade with prognosis in ICU patients with pulmonary edema: a retrospective cohort study and a predictive model based on machine learning.

BMC pulmonary medicine
BACKGROUND: The Albumin-Bilirubin (ALBI) grade was initially used to assess liver reserve function in patients with cirrhosis and has since been applied in the prognostic evaluation of various diseases. This study explored the relationship between th...

New biomarkers to predict the need for surgery of necrotizing enterocolitis: a study based on abdominal X-ray radiomics and machine learning.

Biomedical engineering online
BACKGROUND: Necrotizing enterocolitis (NEC) is an inflammatory intestinal disease that primarily affects premature infants and is a major cause of death in the neonatal period. Approximately half of the affected infants require surgical intervention,...

LAC-TME classifier: machine learning-driven model predicts survival and prioritizes targeted therapy in clear cell renal cell carcinoma.

Journal of cancer research and clinical oncology
BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is a major type of kidney cancer, making up about 80% of cases, with advanced stages showing low survival rates. Current treatments face challenges like toxicity and drug resistance. Studies indicat...

Unveiling potent xanthine oxidase inhibitors in two Balanophora spp. using machine learning-based virtual screening and molecular docking approach.

Scientific reports
Pharmacological studies revealed that the Balanophora species contains diverse phytochemicals which enable interesting biological activities and emphasize their pharmaceutical relevance. Previously, we identified significant xanthine oxidase (XO) inh...

Radiomics-based quantification of tumor infiltration in the non-enhancing peritumoral region on postoperative MRI is associated with survival in glioblastoma.

Scientific reports
Glioblastoma is characterized by diffuse infiltration, making accurate detection of residual disease essential for improving prognostication and guiding treatment. This study evaluates whether the volume of predicted infiltration, generated by a mach...