AIMC Topic: Machine Learning

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Multiparameter MRI-based automatic segmentation and diagnostic models for the differentiation of intracranial solitary fibrous tumors and meningiomas.

Annals of medicine
BACKGROUND: Intracranial solitary fibrous tumors (SFTs) and meningiomas are meningeal tumors with different malignancy levels and prognoses. Their similar imaging features make preoperative differentiation difficult, resulting in high misdiagnosis ra...

Adverse impact of paternal age on embryo euploidy: insights from retrospective analysis and interpretable Machine learning.

Human fertility (Cambridge, England)
The trend of delayed childbearing has increased the average age of parents, with the impact of paternal age on embryo euploidy remaining controversial. Therefore, this study aimed to investigate the impact of paternal age on embryo euploidy using ret...

Detection and quantification of formaldehyde adulteration in cow and buffalo milk using UV-Vis-NIR spectroscopy with machine learning.

Food chemistry
This work uses UV-Vis-NIR spectroscopy (200-1700 nm), spectral preprocessing, principal component analysis (PCA), and machine learning (ML) to identify and quantify formalin adulteration in cow and buffalo milk. Formalin was added to milk at various ...

Electrical grid-independent machine learning-assisted wearable gait analysis device with triboelectric-electromagnetic hybrid energy harvester.

Biosensors & bioelectronics
In this study, an Electrical grid-independent Machine learning-assisted Wearable device for Gait analysis (EMWG) with a ground reaction force sensor is presented. For gait analysis, a multi-layer perceptron is identified as the optimal model among va...

Exploiting the gut microbiota of aquatic animals as indicators of microplastic pollution using interpretable machine learning models.

Journal of hazardous materials
The response of aquatic animal gut microbiota to microplastics has been extensively studied and shows sensitivity, however, the potential of using gut microbiota as indicators for microplastic pollution has not yet been fully explored. To address thi...

The Role of Artificial Intelligence in Surgery: Predictive Analytics, Intraoperative Assistance, and Education.

Anesthesiology clinics
Artificial intelligence (Al) is transforming surgical care by enhancing risk prediction, preoperative planning, and surgical education. Unlike traditional statistical tools, Al-especially machine learning-can process complex, nonlinear clinical data ...

State Ensemble Energy Recognition (SEER): A Hybrid Gas-Phase Molecular Charge State Predictor.

Journal of chemical information and modeling
Accurately resolving a three-dimensional structure that corresponds to an experimental mass spectrometry (MS) result is valuable for outcomes such as improved analyte identification, determination of physiochemical properties relating to conformation...

Optical Resolution of the Morphological Change of Single Nanoparticles at Native Conditions: A Nonsuper-Resolution Approach.

ACS sensors
Label-free optical imaging of the morphology of single nanoparticles under native conditions remains a challenging task despite its importance in the synthesis, properties, and applications of nanomaterials. Here, we developed an angular scanning dar...

A novel method to predict the haemoglobin concentration after kidney transplantation based on machine learning: prediction model establishment and method optimization.

BMC medical informatics and decision making
BACKGROUND: Anaemia is a common complication after kidney transplantation, and the haemoglobin concentration is one of the main criteria for identifying anaemia. Moreover, artificial intelligence methods have developed rapidly in recent years, are wi...

Streamlining medical software development with CARE lifecycle and CARE agent: an AI-driven technology readiness level assessment tool.

BMC medical informatics and decision making
BACKGROUND: Developing medical software requires navigating complex regulatory, ethical, and operational challenges. A comprehensive framework that supports both technical maturity and clinical safety is essential for effective artificial intelligenc...