AIMC Topic: Humans

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IQUP identifies quantitatively unreliable spectra with machine learning for isobaric labeling-based proteomics.

Scientific reports
Mass spectrometry‑based proteomics using isobaric labeling technology has become popular for proteomic quantitation. Existing approaches rely on the mechanism of target-decoy search and false discovery rate control to examine whether a peptide-spectr...

Multimodal feature distinguishing and deep learning approach to detect lung disease from MRI images.

Scientific reports
Precise and early detection and diagnosis of lung diseases reduce the severity of life risk and further spread of infections in patients. Computer-based image processing techniques utilize magnetic resonance imaging (MRI) as input for computing, dete...

Long chain fatty acid transport via SLC27A1 enhances DAG-3-P synthesis and accelerates colorectal cancer metastasis.

Scientific reports
Colorectal cancer (CRC) is a major global health issue. Despite advancements in treatment, CRC patients still face challenges of metastasis and variable prognosis. Circulating tumor cells (CTCs) shed from the primary tumor into the peripheral blood c...

Enhanced glioma semantic segmentation using U-net and pre-trained backbone U-net architectures.

Scientific reports
Gliomas are known to have different sub-regions within the tumor, including the edema, necrotic, and active tumor regions. Segmenting of these regions is very important for glioma treatment decisions and management. This paper aims to demonstrate the...

Optimized hierarchical CLSTM model for sentiment classification of tweets using boosted killer whale predation strategy.

Scientific reports
Opinion mining is more challenging than it was before because of all the user-generated material on social media. People use Twitter (X) to gather opinions on products, advancements, and laws. Sentiment Analysis (SA) examines people's thoughts, feeli...

DCNN models with post-hoc interpretability for the automated detection of glossitis and OSCC on the tongue.

Scientific reports
This study aimed to develop and evaluate deep convolutional neural network (DCNN) models with Grad-CAM visualization for the automated classification with interpretability of tongue conditions-specifically glossitis and oral squamous cell carcinoma (...

Personalized health monitoring using explainable AI: bridging trust in predictive healthcare.

Scientific reports
AI has propelled the potential for moving toward personalized health and early prediction of diseases. Unfortunately, a significant limitation of many of these deep learning models is that they are not interpretable, restricting their clinical utilit...

Adipose tissue gene expression and longitudinal clinical phenotypes are early biomarkers of lipid-regulating drug usage.

Scientific reports
Cardiovascular disease progression is characterised by the dysregulation of lipid metabolism and pro-atherogenic effects of adipose tissue signalling. Recent findings from the analysis of transcriptomic data in bulk tissue has enabled these insights ...

An attention-based mRNA transformer network for accurate prediction of melanoma response to immune checkpoint inhibitors.

Scientific reports
Melanoma immunotherapy urgently requires approaches that can accurately predict drug responses to minimize unnecessary treatments. Deep learning models have emerged as powerful tools in this domain due to their robust predictive capabilities. Integra...

Synthetic data generation method improves risk prediction model for early tumor recurrence after surgery in patients with pancreatic cancer.

Scientific reports
Pancreatic cancer is aggressive with high recurrence rates, necessitating accurate prediction models for effective treatment planning, particularly for neoadjuvant chemotherapy or upfront surgery. This study explores the use of variational autoencode...