AIMC Topic: Machine Learning

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Ethical and Bias Considerations in Artificial Intelligence/Machine Learning.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
As artificial intelligence (AI) gains prominence in pathology and medicine, the ethical implications and potential biases within such integrated AI models will require careful scrutiny. Ethics and bias are important considerations in our practice set...

Exploring phenotypes to improve long-term mortality risk stratification in obstructive sleep apnea through a machine learning approach: an observational cohort study.

European journal of internal medicine
BACKGROUND: Obstructive sleep apnea (OSA) is a heterogeneous sleep disorder for which the identification of phenotypes might help for risk stratification for long-term mortality. Thus, the aim of the study was to identify distinct phenotypes of OSA a...

Machine learning and SHAP value interpretation for predicting comorbidity of cardiovascular disease and cancer with dietary antioxidants.

Redox biology
OBJECTIVE: To develop and validate a machine learning model incorporating dietary antioxidants to predict cardiovascular disease (CVD)-cancer comorbidity and to elucidate the role of antioxidants in disease prediction.

Integration of spectroscopic techniques and machine learning for optimizing Phaeodactylum tricornutum cell and fucoxanthin productivity.

Bioresource technology
The development of sustainable and controlled microalgae bioprocesses relies on robust and rapid monitoring tools that facilitate continuous process optimization, ensuring high productivity and minimizing response times. In this work, we analyse the ...

Novel dilation-erosion labeling technique allows for rapid, accurate and adjustable alignment measurements in primary TKA.

Computers in biology and medicine
BACKGROUND: Optimal implant position and alignment remains a controversial, yet critical topic in primary total knee arthroplasty (TKA). Future study of ideal implant position will require the ability to efficiently measure component positions at sca...

Machine Learning-Engineered Nanozyme System for Synergistic Anti-Tumor Ferroptosis/Apoptosis Therapy.

Small (Weinheim an der Bergstrasse, Germany)
Nanozymes with multienzyme-like activity have sparked significant interest in anti-tumor therapy via responding to the tumor microenvironment (TME). However, the consequent induction of protective autophagy substantially compromises the therapeutic e...

Machine Learning-Aided Inverse Design and Discovery of Novel Polymeric Materials for Membrane Separation.

Environmental science & technology
Polymeric membranes have been widely used for liquid and gas separation in various industrial applications over the past few decades because of their exceptional versatility and high tunability. Traditional trial-and-error methods for material synthe...

Enhancing the estimation of cadmium content in rice leaves by integrating vegetation indices and color indices using machine learning.

Ecotoxicology and environmental safety
Cadmium (Cd) is a heavy metal recognized for its notable biotoxicity. Excessive Cd levels can have detrimental effects on crop growth, development, and yield. Real-time, rapid, and nondestructive monitoring of Cd content in leaves (LCd) is essential ...

Machine-Learning-Enabled Thermochemistry Estimator.

Journal of chemical information and modeling
Modeling adsorbates on single-crystal metals is critical in rational catalyst design and other research that requires detailed thermochemistry. First-principles simulations via density functional theory (DFT) are among the prevalent tools to acquire ...

Size-Coded Hydrogel Microbeads for Extraction-Free Serum Multi-miRNAs Quantifications with Machine-Learning-Aided Lung Cancer Subtypes Classification.

Nano letters
Classifying lung cancer subtypes, which are characterized by multi-microRNAs (miRNAs) upregulation, is important for therapy and prognosis evaluation. Liquid biopsy is a promising approach, but the pretreatment of RNA extraction is labor-intensive an...