AIMC Topic: Adult

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A dual recurrent neural network model of human-like motion for artificial agents and its evaluation in a VR mirror game turing test.

Scientific reports
Action-oriented approaches to cognition which emphasize the constitutive role of sensorimotor patterns for perception are gaining importance for the study of cognitive processes in the human brain as well as for endowing artificial agents with cognit...

The influence of AI service robots' humorous response strategies on consumer forgiveness following service failure.

Scientific reports
As technology advances, more AI entities are deployed in public service roles. However, AI service robot failures are increasingly frequent, causing negative behaviors such as customer dissatisfaction or complaints. Service recovery plays a crucial r...

Perceptions of portable dentistry in Asia using machine learning models.

Scientific reports
Access to healthcare is a significant challenge for individuals with limited mobility, particularly in developing countries and among vulnerable populations in Asia. Portable dentistry offers an innovative solution by delivering essential dental serv...

Optimizing machine learning models for predicting health service access and determinants among pregnant women in rural Ethiopia.

Scientific reports
Pregnant women in rural Ethiopia face substantial barriers to accessing adequate healthcare services, contributing to adverse maternal and neonatal health outcomes. Traditional statistical approaches often fall short in capturing the complex, nonline...

An assisted diagnostic and prognostic model for endometrial cancer using 36 serological markers and clinical variables from 562 patients.

Scientific reports
Endometrial carcinoma (EC) has demonstrated a concerning epidemiological trajectory. Current evaluation systems for EC are limited to postoperative analysis, necessitating the development of a preoperative risk stratification model. Researchers aimed...

Identify MRI negative temporal lobe epilepsy with resting fMRI indicators and machine learning techniques.

Scientific reports
About 30% of temporal lobe epilepsy (TLE) cases are negative on MRI, so quantitative diagnosis based on clinical symptoms becomes challenging. There is an urgent need for an accurate and reliable method to differentiate patients with MRI-negative TLE...

Prefrontal-bed nucleus of the stria terminalis physiological and neuropsychological biomarkers predict therapeutic outcomes in depression.

Nature communications
Therapeutic options for refractory depression are urgently needed. We conducted a deep brain stimulation (DBS) randomized controlled trial of the bed nucleus of the stria terminalis (BNST), an extended amygdala structure, and nucleus accumbens (NAc) ...

Multimodal AI and tumour microenvironment integration predicts metastasis in cutaneous melanoma.

Nature communications
Accurate prognostication is essential to guide clinical management in localised cutaneous melanoma (CM), the form of skin cancer with the highest mortality. While the tumour microenvironment (TME) plays a key role in disease progression, current stag...

Development and external validation of a machine learning model to predict high flow nasal cannula failure.

BMJ open respiratory research
INTRODUCTION: High-flow nasal cannula (HFNC) is an important treatment option for acute hypoxic respiratory failure and can improve outcomes. However, patients on a prolonged duration of HFNC have worse clinical outcomes and increased mortality. It i...

Predicting distant metastasis in early-onset kidney cancer using machine learning: a SEER database study with external validation.

Clinical and experimental medicine
Patients with early-onset kidney cancer (EOKC) face a marked decline in prognosis after distant metastasis, yet the accuracy of current predictive methods remains limited. This study aims to develop a predictive model using multiple machine learning ...