AIMC Topic: Humans

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Development of an oral cancer detection system through deep learning.

BMC oral health
OBJECTIVE: We aimed to develop an AI-based model that uses a portable electronic oral endoscope to capture intraoral images of patients for the detection of oral cancer.

Prediction of preterm birth using machine learning: a comprehensive analysis based on large-scale preschool children survey data in Shenzhen of China.

BMC pregnancy and childbirth
BACKGROUND: Preterm birth (PTB) is a significant cause of neonatal mortality and long-term health issues. Accurate prediction and timely prevention of PTB are essential for reducing associated child mortality and morbidity. Traditional predictive met...

Transformers significantly improve splice site prediction.

Communications biology
Mutations that affect RNA splicing significantly impact human diversity and disease. Here we present a method using transformers, a type of machine learning model, to detect splicing from raw 45,000-nucleotide sequences. We generate embeddings with r...

Eeg based smart emotion recognition using meta heuristic optimization and hybrid deep learning techniques.

Scientific reports
In the domain of passive brain-computer interface applications, the identification of emotions is both essential and formidable. Significant research has recently been undertaken on emotion identification with electroencephalogram (EEG) data. The aim...

Revolutionizing healthcare: a comparative insight into deep learning's role in medical imaging.

Scientific reports
Recently, Deep Learning (DL) models have shown promising accuracy in analysis of medical images. Alzeheimer Disease (AD), a prevalent form of dementia, uses Magnetic Resonance Imaging (MRI) scans, which is then analysed via DL models. To address the ...

Machine learning evaluation of a hypertension screening program in a university workforce over five years.

Scientific reports
The global prevalence of hypertension continues excessively elevated, especially among low- and middle-income nations. Workplaces provide tremendous opportunities as a unique, easily accessible and practical avenue for early diagnosis and treatment o...

AI depictions of psychiatric diagnoses: a preliminary study of generative image outputs in Midjourney V.6 and DALL-E 3.

BMJ mental health
OBJECTIVE: This paper investigates how state-of-the-art generative artificial intelligence (AI) image models represent common psychiatric diagnoses. We offer key lessons derived from these representations to inform clinicians, researchers, generative...

Strategies for creation of data reserve and stress testing of medical AI products.

BMJ health & care informatics
With the fast development of artificial intelligence (AI) and its applications in medicine, it is often said that the time for intelligent medicine is arriving, if not already have arrived. While there is no doubt that AI-centred intelligent medicine...

Performance of machine learning versus the national early warning score for predicting patient deterioration risk: a single-site study of emergency admissions.

BMJ health & care informatics
OBJECTIVES: Increasing operational pressures on emergency departments (ED) make it imperative to quickly and accurately identify patients requiring urgent clinical intervention. The widespread adoption of electronic health records (EHR) makes rich fe...

Insights From Art Therapists on Using AI-Generated Art in Art Therapy: Mixed Methods Study.

JMIR formative research
BACKGROUND: With the increasing integration of artificial intelligence (AI) into various aspects of daily life, there is a growing interest among designers and practitioners in incorporating AI into their fields. In health care domains like art thera...