AIMC Topic: Humans

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An explainable transformer model for Alzheimer's disease detection using retinal imaging.

Scientific reports
Alzheimer's disease (AD) is a neurodegenerative disorder that affects millions worldwide. In the absence of effective treatment options, early diagnosis is crucial for initiating management strategies to delay disease onset and slow down its progress...

Diabetes diagnosis using a hybrid CNN LSTM MLP ensemble.

Scientific reports
Diabetes is a chronic condition brought on by either an inability to use insulin effectively or a lack of insulin produced by the body. If left untreated, this illness can be lethal to a person. Diabetes can be treated and a good life can be led with...

Public hesitancy for AI-based detection of neurodegenerative diseases in France.

Scientific reports
Recent advances in artificial intelligence (AI) have made it possible to detect neurodegenerative diseases (NDDs) earlier, potentially improving patient outcomes. However, AI-based detection tools remain underutilized. We studied individual valuation...

Machine learning driven diabetes care using predictive-prescriptive analytics for personalized medication prescription.

Scientific reports
The increasing prevalence of type 2 diabetes (T2D) is a significant health concern worldwide. Effective and personalized treatment strategies are essential for improving patient outcomes and reducing healthcare costs. Machine learning (ML) has the po...

Histology image analysis of 13 healthy tissues reveals molecular-histological correlations.

Scientific reports
Gene expression is an important process in which genes guide the synthesis of proteins, and molecular-level differences often lead to individual phenotypic variations. Combining molecular information at the nano-level with phenotypic information at t...

Development and validation of a deep learning image quality feedback system for infant fundus photography.

Scientific reports
Retinopathy of prematurity (ROP) is a significant cause of childhood blindness. Many healthcare institutions face a shortage of well-trained ophthalmologists for conducting screenings. Hence, we have developed the Deep Learning Infant Fundus Quality ...

A new framework for mental illnesses diagnosis using wearable devices aided by improved convolutional neural network.

Scientific reports
Stress inherent in the modern world is considered one of the main causes of Mental Health Disorders (MHDs) that spread in every country around the world. These mental and behavioral problems primarily affect the mind and brain that change emotions an...

Early and non-destructive prediction of the differentiation efficiency of human induced pluripotent stem cells using imaging and machine learning.

Scientific reports
The reproducibility and robustness of many directed differentiation protocols from human induced pluripotent stem cells (hiPSCs) remain low, and the long differentiation induction period significantly limits protocol optimization. To address this, we...

Multilingual identification of nuanced dimensions of hope speech in social media texts.

Scientific reports
Hope plays a crucial role in human psychology and well-being, yet its expression and detection across languages remain underexplored in natural language processing (NLP). This study presents MIND-HOPE, the first-ever multiclass hope speech detection ...

Large-vocabulary forensic pathological analyses via prototypical cross-modal contrastive learning.

Nature communications
Forensic pathology plays a vital role in determining the cause and manner of death through macroscopic and microscopic post-mortem examinations. However, the field faces challenges such as variability in outcomes, labor-intensive processes, and a sho...