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
Jul 8, 2025
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)
Jul 8, 2025
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...
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
Jul 8, 2025
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
Jul 8, 2025
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...
Machine learning-based QSAR and structure-based virtual screening guided discovery of novel mIDH1 inhibitors from natural products.
Journal of computer-aided molecular design
Jul 8, 2025
Mutations in isocitrate dehydrogenase 1 (IDH1) have been widely observed in various tumors, such as gliomas and acute myeloid leukemia, and therefore has become one of the current research focal points. Therefore, it is crucial to find inhibitors tha...
Machine learning assisted adjustment boosts efficiency of exact inference in randomized controlled trials.
Scientific reports
Jul 8, 2025
In this work, we proposed a novel inferential procedure assisted by machine learning based adjustment for randomized control trials. The method was developed under the Rosenbaum's framework of exact tests in randomized experiments with covariate adju...
Integrated analysis of WGCNA and machine learning identified diagnostic biomarkers in trauma-induced coagulopathy.
Scientific reports
Jul 8, 2025
Despite advancements in trauma care, uncontrolled hemorrhage and trauma-induced coagulopathy (TIC) remain the leading causes of preventable deaths after trauma. Understanding the genetic underpinnings and molecular mechanisms of TIC is crucial for de...
Effectiveness of machine learning models in diagnosis of heart disease: a comparative study.
Scientific reports
Jul 8, 2025
The precise diagnosis of heart disease represents a significant obstacle within the medical field, demanding the implementation of advanced diagnostic instruments and methodologies. This article conducts an extensive examination of the efficacy of di...
Machine learning-assisted early detection of keratoconus: a comparative analysis of corneal topography and biomechanical data.
Scientific reports
Jul 8, 2025
Keratoconus is a progressive eye disease characterized by the thinning and bulging of the cornea, leading to visual impairment. Early and accurate diagnosis is crucial for effective management and treatment. This study investigates the application of...
Application of multimodal machine learning-based analysis for the biomethane yields of NaOH-pretreated biomass.
Scientific reports
Jul 8, 2025
This study investigated the impact of alkaline pretreatment on the biomethane yield of Xyris capensis experimentally and computationally using machine-learning (ML)-based techniques. Despite extensive studies on the anaerobic digestion of lignocellul...
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