AIMC Topic: Humans

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Enhanced early skin cancer detection through fusion of vision transformer and CNN features using hybrid attention of EViT-Dens169.

Scientific reports
Early diagnosis of skin cancer remains a pressing challenge in dermatological and oncological practice. AI-driven learning models have emerged as powerful tools for automating the classification of skin lesions by using dermoscopic images. This study...

Decision tree-based machine learning methods for identifying colorectal cancer-associated microRNA signatures and their regulatory networks.

Scientific reports
This study aimed to identify candidate diagnostic miRNAs from the serum of colorectal cancer (CRC) patients using Boruta, a wrapper-based feature selection technique, in combination with decision tree-based machine learning methods. We analyzed three...

Comparative estimation of the spread of acute diarrhea and dengue in India using statistical mathematical and deep learning models.

Scientific reports
This study aims to forecast the spread of acute diarrhoea and dengue diseases in India by conducting a comparative analysis of statistical, mathematical (compartmental), and deep learning time series models. Utilizing weekly reported cases and fatali...

Comprehensive brain tumour concealment utilizing peak valley filtering and deeplab segmentation.

Scientific reports
Brain tumour identification, segmentation cataloguing from MRI images is most thought-provoking and is a very much essential for many medical image analysis applications. Every brain imaging modality provides information about various parts of the tu...

The power of justifications to repair human-robot trust, even under moral disagreement.

Scientific reports
To avert criticism and losses of trust, robots that adopt social roles in the near future will have to be aware of and follow the norms of the communities in which they operate. However, norms often conflict with one another, and resolving such confl...

Predictive Coding Light.

Nature communications
Current machine learning systems consume vastly more energy than biological brains. Neuromorphic systems aim to overcome this difference by mimicking the brain's information coding via discrete voltage spikes. However, it remains unclear how both art...

Reconfiguration of functional brain hierarchy in schizophrenia.

Translational psychiatry
The multidimensional nature of schizophrenia requires a comprehensive exploration of the functional and structural brain networks. While prior research has provided valuable insights into these aspects, our study goes a step further to investigate th...

Role of the rostral anterior cingulate cortex in emotion processing in Treatment Resistant Depression.

Translational psychiatry
The rostral anterior cingulate cortex (rACC) has been identified as a key region in treatment-resistant depression (TRD), potentially influencing the adaptive interplay between the default mode network and other critical neural networks. This study a...

AI-driven protein pocket detection through integrating deep Q-networks for structural analysis.

Journal of computer-aided molecular design
Protein pockets, or small cavities on the protein surface, are critical sites for enzymatic catalysis, molecular recognition, and drug binding. Accurately identifying these pockets is crucial for understanding protein function and designing therapeut...

Applications of machine learning in deep brain stimulation for major depressive disorder: a systematic review and meta-analysis.

Neurosurgical review
Depression is a significant public health issue, consistently ranking among the leading causes of mortality, reduced quality of life, and economic burden. Despite available treatments, approximately one-third of patients exhibit resistance to standar...