AIMC Topic: Humans

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Classification of cervical cancer using Dense CapsNet with Seg-UNet and denoising autoencoders.

Scientific reports
Cervical cancer is one of the deadly diseases that affects women, which requires periodic examinations to identify and treat any cancerous tumors at a preliminary stage. The most prevalent examination tool for cervical cancer prompt identification is...

Predicting patients' sentiments about medications using artificial intelligence techniques.

Scientific reports
The increasing development of technology has led to the increase of digital data in various fields, such as medication-related texts. Sentiment Analysis (SA) in medication is essential to give clinicians insights into patients' feedback about the tre...

Radiomics for differentiating adenocarcinoma and squamous cell carcinoma in non-small cell lung cancer beyond nodule morphology in chest CT.

Scientific reports
Distinguishing between primary adenocarcinoma (AC) and squamous cell carcinoma (SCC) within non-small cell lung cancer (NSCLC) tumours holds significant management implications. We assessed the performance of radiomics-based models in distinguishing ...

A deep learning-based ADRPPA algorithm for the prediction of diabetic retinopathy progression.

Scientific reports
As an alternative to assessments performed by human experts, artificial intelligence (AI) is currently being used for screening fundus images and monitoring diabetic retinopathy (DR). Although AI models can provide quasi-clinician diagnoses, they rar...

A machine learning-based clinical predictive tool to identify patients at high risk of medication errors.

Scientific reports
A medication error is an inadvertent failure in the drug therapy process that can cause serious harm to patients by increasing morbidity and mortality and are associated with significant economic costs to the healthcare system. Medication reconciliat...

Identification of sepsis-associated encephalopathy biomarkers through machine learning and bioinformatics approaches.

Scientific reports
Sepsis-associated encephalopathy (SAE) is common in septic patients, characterized by acute and long-term cognitive impairment, and is associated with higher mortality. This study aimed to identify SAE-related biomarkers and evaluate their diagnostic...

Analysis of diagnostic genes and molecular mechanisms of Crohn's disease and colon cancer based on machine learning algorithms.

Scientific reports
Crohn's disease (CD) is a chronic inflammatory bowel condition, and colon adenocarcinoma (COAD), as one of the most prevalent malignant tumors of the digestive tract, has been indicated by research to have a close association with CD. This study empl...

Utilising AI technique to identify depression risk among doctoral students.

Scientific reports
The phenomenon that the depression risk among doctoral students is higher than that of other groups should not be ignored. Despite this, studies specifically addressing depression risk in doctoral students are relatively scarce, and existing findings...

Prediction of prognosis in patients with cerebral contusions based on machine learning.

Scientific reports
Traumatic brain injury (TBI) is a global issue and a major cause of patient mortality, and cerebral contusions (CCs) is a common primary TBI. The haemorrhagic progression of a contusion (HPC) poses a significant risk to patients' lives, and effective...

Deep-learning-based extraction of circle of Willis topology with anatomical priors.

Scientific reports
The circle of Willis (CoW) is a circular arrangement of arteries in the human brain, exhibiting significant anatomical variability. The CoW is extensively studied in relation to neurovascular pathologies, with certain anatomical variants previously l...