AIMC Topic: Humans

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Comparison of in vitro migration assays evaluating nintedanib's migration inhibitory effects on melanoma cells.

Scientific reports
Cell migration plays a central role in tumor progression and metastasis, making it a critical parameter in both cancer biology and therapeutic evaluation. A range of in vitro migration assays are commonly used to assess treatment-induced effects on m...

Development and influencing factors of artificial intelligence literacy and computational thinking in Chinese university students.

Scientific reports
This study investigates the developmental status and influencing factors of artificial intelligence (AI) literacy and computational thinking (CT) literacy among undergraduates in China's "four new" majors. Guided by the Technology Acceptance Model, S...

Predictive biomarkers validation of CD3 cell apheresis yield in CAR-T manufacturing for diffuse large B-cell lymphoma: a machine learning approach.

Scientific reports
Chimeric antigen receptor (CAR) T-cell therapy has shown significant success in treating diffuse large B-cell lymphoma (DLBCL). The initial step involves collecting autologous CD3 lymphocytes through apheresis, in which obtaining an adequate CD3 cell...

Visual cortex speckle imaging for shape recognition.

Scientific reports
This study introduces a non‑invasive approach for neurovisual classification of geometric shapes by capturing and decoding laser‑speckle patterns reflected from the human striate cortex. Using a fast digital camera and deep neural networks (DNN), we ...

Survival machine learning models for predicting all-cause and case-specific mortality risk in metabolic dysfunction-associated fatty liver disease patients.

Scientific reports
Emerging evidence links metabolic dysfunction-associated fatty liver disease (MAFLD) with increased all-cause and circulatory system disease (CSD) mortality in adults, yet survival machine learning studies are limited. This study analyzed 4415 NHANES...

Computed tomography-based nnU-Net for region-specific brain structural changes across the alzheimer's continuum and frontotemporal dementia subtypes.

Scientific reports
Quantifying structural brain changes is critical for diagnosing and monitoring neurodegenerative diseases. Although magnetic resonance imaging (MRI) is the silver standard, limited accessibility and cost hamper routine use. We developed a deep learni...

Enhanced hybrid deep neural network for EEG-based schizophrenia diagnosis using functional and temporal features.

Scientific reports
Schizophrenia is a complex psychiatric disorder that disrupts cognition, emotions, and social behavior. Timely and accurate diagnosis is essential for effective treatment. Traditional diagnostic methods relying on clinical assessments have limitation...

Context matters in machine learning based disease prediction with insights from diverse clinical and symptom data.

Scientific reports
Machine learning (ML) has the potential to drastically improve clinical decision-making by predicting diseases early, accurately, and based on data. This study evaluated and compared the performance of several machine learning models, including a fee...

Development and validation of an interpretable predictive machine learning model for successful weaning of continuous renal replacement therapy.

Scientific reports
Continuous renal replacement therapy (CRRT) is a vital intervention for critically ill patients with severe acute kidney injury, yet no standardized criteria exist to determine the optimal time for its discontinuation. We developed and validated mach...

AI meets endodontics a deep learning approach to precision diagnosis.

Scientific reports
Endodontic illnesses affect around 52% of the global population and are projected to rise by 4% by 2030. Endodontic problems necessitate precise classification for treatment planning and clinical decision-making. Radiographs and expert analysis are e...