AIMC Topic: Humans

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Application-driven validation of posteriors in inverse problems.

Medical image analysis
Current deep learning-based solutions for image analysis tasks are commonly incapable of handling problems to which multiple different plausible solutions exist. In response, posterior-based methods such as conditional Diffusion Models and Invertible...

Dynamic graph based weakly supervised deep hashing for whole slide image classification and retrieval.

Medical image analysis
Recently, a multi-scale representation attention based deep multiple instance learning method has proposed to directly extract patch-level image features from gigapixel whole slide images (WSIs), and achieved promising performance on multiple popular...

Explainable machine learning model for assessing health status in patients with comorbid coronary heart disease and depression: Development and validation study.

International journal of medical informatics
BACKGROUND: Coronary heart disease (CHD) and depression frequently co-occur, significantly impacting patient outcomes. However, comprehensive health status assessment tools for this complex population are lacking. This study aimed to develop and vali...

The feasibility of using machine learning to predict COVID-19 cases.

International journal of medical informatics
BACKGROUND: Coronavirus Disease 2019 (COVID-19), caused by the SARS-CoV-2 virus, emerged as a global health crisis in 2019, resulting in widespread morbidity and mortality. A persistent challenge during the pandemic has been the accuracy of reported ...

Breast radiation therapy fluence painting with multi-agent deep reinforcement learning.

Medical physics
BACKGROUND: The electronic compensation (ECOMP) technique for breast radiation therapy provides excellent dose conformity and homogeneity. However, the manual fluence painting process presents a challenge for efficient clinical operation.

Application of elastic net for clinical outcome prediction and classification in progressive supranuclear palsy: A multicenter cohort study.

Parkinsonism & related disorders
BACKGROUND: Previous studies have used machine learning to identify clinically relevant atrophic regions in progressive supranuclear palsy (PSP). This study applied Elastic Net (EN) in PSP to uncover key atrophic patterns, offering a novel approach t...

Novel machine learning applications in peripartum care: a scoping review.

American journal of obstetrics & gynecology MFM
OBJECTIVE: Machine learning (ML), a subtype of artificial intelligence (AI), presents predictive modeling and dynamic diagnostic tools to facilitate early interventions and improve decision-making. Considering the global challenges of maternal, fetal...

Monkeypox diagnosis based on probabilistic K-nearest neighbors (PKNN) algorithm.

Computers in biology and medicine
Although it is not a new illness and has been around since the previous century, monkeypox later resurgence is fraught with difficulties. This study presents a novel approach of diagnosing monkeypox using artificial intelligence, which is called Effe...

The intelligent brain and the energy heart: Synergistic evolution of artificial intelligence and energy storage technology in China.

Acta psychologica
In the context of China's ongoing industrial revolution and technological transformation, there is a growing demand for advanced energy management solutions and the increasing role of artificial intelligence in various industries. This paper aims to ...

Exploring the association between personality traits and colour saturation preference using machine learning.

Acta psychologica
Both personality traits and colour saturation are associated with emotion; however, how colour saturation preference interacts with different traits and whether this interaction is modulated by object-colour relations remains unclear. In this study, ...