AIMC Topic: Humans

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Development and validation of radiology-clinical statistical and machine learning model for stroke-associated pneumonia after first intracerebral haemorrhage.

BMC pulmonary medicine
BACKGROUND: Society is burdened with stroke-associated pneumonia (SAP) after intracerebral haemorrhage (ICH). Cerebral small vessel disease (CSVD) complicates clinical manifestations of stroke. In this study, we redefined the CSVD burden score and in...

Disparities in medical recommendations from AI-based chatbots across different countries/regions.

Scientific reports
This study explores disparities and opportunities in healthcare information provided by AI chatbots. We focused on recommendations for adjuvant therapy in endometrial cancer, analyzing responses across four regions (Indonesia, Nigeria, Taiwan, USA) a...

Insights from EEG analysis of evoked memory recalls using deep learning for emotion charting.

Scientific reports
Affect recognition in a real-world, less constrained environment is the principal prerequisite of the industrial-level usefulness of this technology. Monitoring the psychological profile using smart, wearable electroencephalogram (EEG) sensors during...

Robust evaluation of deep learning-based representation methods for survival and gene essentiality prediction on bulk RNA-seq data.

Scientific reports
Deep learning (DL) has shown potential to provide powerful representations of bulk RNA-seq data in cancer research. However, there is no consensus regarding the impact of design choices of DL approaches on the performance of the learned representatio...

Adaptative machine vision with microsecond-level accurate perception beyond human retina.

Nature communications
Visual adaptive devices have potential to simplify circuits and algorithms in machine vision systems to adapt and perceive images with varying brightness levels, which is however limited by sluggish adaptation process. Here, the avalanche tuning as f...

NVIDIA's "Chat with RTX" Custom Large Language Model and Personalized AI Chatbot Augments the Value of Electronic Dermatology Reference Material.

JMIR dermatology
This paper demonstrates a new, promising method using generative artificial intelligence (AI) to augment the educational value of electronic textbooks and research papers (locally stored on user's machine) and maximize their potential for self-study,...

Merging sociality and robotics through an evolutionary perspective.

Science robotics
Robotics, using social mechanisms like hormonal modulation, may accelerate our understanding of core sociality principles.

Predicting hospital admissions for upper respiratory tract complaints: An artificial neural network approach integrating air pollution and meteorological factors.

Environmental monitoring and assessment
This study uses artificial neural networks (ANNs) to examine the intricate relationship between air pollutants, meteorological factors, and respiratory disorders. The study investigates the correlation between hospital admissions for respiratory dise...

Interpretable machine learning model based on clinical factors for predicting muscle radiodensity loss after treatment in ovarian cancer.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
PURPOSE: Muscle radiodensity loss after surgery and adjuvant chemotherapy is associated with poor outcomes in ovarian cancer. Assessing muscle radiodensity is a real-world clinical challenge owing to the requirement for computed tomography (CT) with ...