AIMC Topic: Humans

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BCECNN: an explainable deep ensemble architecture for accurate diagnosis of breast cancer.

BMC medical informatics and decision making
BACKGROUND: Breast cancer remains one of the leading causes of cancer-related deaths globally, affecting both women and men. This study aims to develop a novel deep learning (DL)-based architecture, the Breast Cancer Ensemble Convolutional Neural Net...

GPT-4o and the quest for machine learning interpretability in ICU risk of death prediction.

BMC medical informatics and decision making
BACKGROUND: Clinical utilization of machine learning is hampered by the lack of interpretability inherent in most non-linear black box modeling approaches, reducing trust among clinicians and regulators. Advanced large language models offer a potenti...

A mixture of experts (MoE) model to improve AI-based computational pathology prediction performance under variable levels of image blur.

BMC medical imaging
BACKGROUND: AI-based models for analysis of histopathology whole slide images (WSIs) are now common. However, image quality, particularly unsharp areas of WSIs, impacts model performance. In this study we investigate the impact of blur on deep learni...

Assessment of ChatGPT performance in orbital MRI reporting with multimetric evaluation of transformer based language models.

Scientific reports
Transformer-based large language models (LLMs), such as ChatGPT-4, are increasingly used to streamline clinical practice, of which radiology reporting is a prominent aspect. However, their performance in interpreting complex anatomical regions from M...

Study on rural landscape design strategies integrating computer vision and deep learning: an analysis based on human perception and visual aesthetics.

Scientific reports
With the increasing application of artificial intelligence in environmental design, computer vision and deep learning have emerged as crucial tools for understanding human visual perception. This study focuses on rural landscapes and proposes a visua...

Single-cell RNA sequencing and Mendelian randomization, revealing molecular mechanisms and causal correlation of immune-related genes in periodontitis.

Scientific reports
The immune system has been linked to periodontitis risk in oral inflammation and systemic consequences. Specifically, this study investigated whether hub genes were associated with immune cells via integrating single-cell RNA sequencing (scRNA-seq) a...

AI-driven drug discovery using a context-aware hybrid model to optimize drug-target interactions.

Scientific reports
Drug discovery is a challenging and resource-intensive process characterized by high costs, prolonged development timelines, and regulatory hurdles in the pharmaceutical sector. AI-driven recommendation systems have emerged as an effective approach t...

A multimodal multipath AI system for assessing PAH after VSD correction on echocardiography and chest radiography images.

Scientific reports
Developing a novel artificial intelligence (AI) system that can automatically detect pulmonary arterial hypertension (PAH) after correcting the ventricular septal defect (VSD) and to help clinicians make reasonable treatment plans. We analyzed data f...

The exhaled breath pattern as a potential method for biometrics identification.

Scientific reports
Conventional biometric identification methods relying on Personally Identifiable Information (PII) pose significant challenges concerning privacy and security. Volatile organic compounds (VOCs) in exhaled breath are unique to individuals and can serv...

Assessment of an unsupervised denoising approach based on Noise2Void in digital mammography.

Scientific reports
Full-field digital mammography (FFDM) is the most common imaging technique for breast cancer screening programs. Still, it is limited by noise from quantum effects, electronic issues, and X-ray scattering, affecting the image quality. Traditional den...