AIMC Topic: Machine Learning

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Using digital archaeology and machine learning to determine sex in finger flutings.

Scientific reports
One of the earliest and most enigmatic forms of rock art are finger flutings and previous methods of studying them relied on biometric finger ratios from modern populations to make assumptions about the people who left the flutings, which is theoreti...

Machine learning identifies MiRNA biomarkers and immune mechanisms in active tuberculosis.

Scientific reports
Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a major global public health threat. The rising prevalence of HIV/TB co-infection and multidrug-resistant tuberculosis (MDR-TB) has further intensified this challenge. This study ...

Investigating environmental determinants and spatiotemporal dynamics of highly pathogenic avian influenza H5N1 outbreaks in India through machine learning.

Scientific reports
Avian Influenza (AI), caused by highly pathogenic strains of influenza viruses, poses a significant threat to poultry populations and public health worldwide. This study offers a comprehensive evaluation of the spatial and temporal dynamics of HPAI o...

Differential responses of Cacao pathogens Colletotrichum gloeosporioides and Pestalotiopsis sp. to UVB 305 nm and UVC 275 nm.

Scientific reports
Sustainable control of microbial pathogens requires alternatives to chemical agents. However, the efficacy of physical methods like Ultraviolet-C (UVC) radiation is often inconsistent due to poorly understood, pathogen-specific resistance mechanisms....

Enhancing explainability in epidemiological predictions using fuzzy logic integrated with machine and deep learning algorithms.

Scientific reports
Epidemiological data is often analyzed without fully accounting for the uncertainties that are key to understanding the nuances of the dataset. While traditional approaches like the SIR mathematical model provide valuable insights, our study aims to ...

Modelling of immune infiltration in prostate cancer treated with HDR-brachytherapy using Raman spectroscopy and machine learning.

Scientific reports
Prostate cancer is characterized by an immunosuppressive tumour environment. This work combines Raman spectroscopy with group-and-bases-restricted non-negative matrix factorization (GBR-NMF) and machine learning to assemble models of immune cell dens...

Development and validation of a predictive model for diabetic peripheral neuropathy with type 2 diabetes mellitus in Xinjiang, China.

Scientific reports
This study aims to identify risk factors associated with diabetic peripheral neuropathy (DPN) in patients with type 2 diabetesmellitus (T2DM) and to develop a predictive model to support clinical decision-making. A total of 1,001 patients with T2DM w...

Backtracking metabolic dynamics in single cells predicts bacterial replication in human macrophages.

Nature communications
Accurately tracking dynamic state transitions is crucial for modeling and predicting biological outcomes, as it captures heterogeneity of cellular responses. To build a model to predict bacterial infection in single cells, we have monitored in parall...

A Machine Learning-Based Scoring System to Identify High Immunoactivity Microsatellite Stability Tumors by Quantifying Similarity to Microsatellite Instability-High Tumors in Colorectal Cancers: Development and Quantitative Study.

JMIR formative research
BACKGROUND: Microsatellite stability (MSS) colorectal cancers (CRCs) have a limited response to immune checkpoint inhibitors (ICIs) compared to microsatellite instability-high (MSI-H) CRCs. Nevertheless, previous studies have shown that some MSS CRCs...

Retinal microvascular differences between multiple sclerosis and neuromyelitis optica spectrum disorder: a cross-sectional study with diagnostic modeling.

Journal of neurology
BACKGROUND AND OBJECTIVES: Retinal alterations in multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) remain unclear, especially the specific patterns and extent of microvascular change. This study aimed to compare these altera...