AIMC Topic: Humans

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Multi-omics analysis identifies SNP-associated immune-related signatures by integrating Mendelian randomization and machine learning in hepatocellular carcinoma.

Scientific reports
Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death globally, characterized by high morbidity and poor prognosis. The complex molecular and immune landscape of HCC makes accurate patient stratification and personalized treatment...

Sperm metabolomic signatures of asthenozoospermia and teratozoospermia in Chinese reproductive-age men.

Scientific reports
Asthenozoospermia and teratozoospermia are common causes of male infertility. Despite their prevalence, the underlying metabolic mechanisms remain poorly understood. In this study, we conducted targeted metabolomic profiling of sperm samples from 131...

CNN based method for classifying cervical cancer cells in pap smear images.

Scientific reports
The absence of reliable early treatment serves as one of the main causes of cervical cancer. Hence, it is crucial to detect cervical cancer early. The biggest challenge in diagnosing cervical cancer early is that it is asymptomatic until it develops ...

MultiFG: integrating molecular fingerprints and graph embeddings via attention mechanisms for robust drug side effect prediction.

Scientific reports
Accurate prediction of drug side effect frequencies is critical for drug safety assessment but remains challenging due to the high cost of clinical trials and the limited generalizability of existing models. We propose Multi Fingerprint and Graph Emb...

Neural network assisted annotation and analysis tool to study in-vivo foveolar cone photoreceptor topography.

Scientific reports
The foveola, the central region of the human retina, plays a crucial role in sharp color vision and is challenging to study due to its unique anatomy and technical limitations in imaging. We present ConeMapper, an open-source MATLAB software that int...

Intelligent brain tumor detection using hybrid finetuned deep transfer features and ensemble machine learning algorithms.

Scientific reports
Brain tumours (BTs) are severe neurological disorders. They affect more than 308,000 people each year worldwide. The mortality rate is over 251,000 deaths annually (IARC, 2020 reports). Detecting BTs is complex because they vary in nature. Early diag...

A robust machine learning approach to predicting remission and stratifying risk in rheumatoid arthritis patients treated with bDMARDs.

Scientific reports
Rheumatoid arthritis (RA) is a chronic autoimmune disease affecting millions worldwide, leading to inflammation, joint damage, and reduced quality of life. Although biological disease-modifying antirheumatic drugs (bDMARDs) are effective, they are co...

Predictive analysis of pediatric gastroenteritis risk factors and seasonal variations using VGG Dense HybridNetClassifier a novel deep learning approach.

Scientific reports
Pediatric gastroenteritis is a major reason for sickness and death among children worldwide, especially in places where healthcare and clean sanitation are scarce. Conventional methods of diagnosis overlook possible risks and seasonal trends, which r...

Multi-strategy enhanced artificial rabbits optimization for prediction of grades in tourism service communication courses.

Scientific reports
Predicting students' grades through their classroom behavior has been a longstanding concern in education. Recently, artificial intelligence has demonstrated remarkable potential in this area. In this study, the Artificial Rabbits Optimization Algori...

Leveraging pathological markers of lower grade glioma to predict the occurrence of secondary epilepsy, a retrospective study.

Scientific reports
Epilepsy is a common manifestation in patients with lower grade glioma (LGG), often presenting as the initial symptom in approximately 70% of cases. This study aimed to identify clinical and pathological markers for epileptic seizures in patients wit...