AIMC Topic: Humans

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Artificial intelligence derived grading of mustard gas induced corneal injury and opacity.

Scientific reports
Artificial intelligence (AI) has emerged as a transformative tool in ophthalmology for disease diagnosis and prognosis. However, use of AI for assessing corneal damage due to chemical injury in live rabbits remains lacking. This study aimed to develo...

Developed a knowledge base of risk factors for postoperative cognitive dysfunction: a retrospective database study.

Scientific reports
Postoperative cognitive dysfunction (POCD), a heterogeneous spectrum of surgery/anesthesia-associated neurocognitive impairments, represents a critical clinical challenge due to its associations with prolonged hospitalization, increased mortality, an...

Fabrication of serum-based SERS-tailored 3D structures for thyroid cancer diagnosis.

Scientific reports
Early detection of thyroid cancer improves patient survival rate from 51.9% to 99.9%. Fine needle aspiration cytology is the primary method for diagnosing thyroid cancer; however, this method is associated with limitations, including diagnostic uncer...

An enhanced deep learning model for accurate classification of ovarian cancer from histopathological images.

Scientific reports
Ovarian Cancer is a malignancy that develops from ovarian cells and is frequently characterized by aberrant cell proliferation that leads to the creation of tumors within the ovaries. The high death rate and often delayed discovery of Ovarian Cancer ...

Proteomic risk scores for predicting common diseases using linear and neural network models in the UK biobank.

Scientific reports
Plasma proteomics provides a unique opportunity to enhance disease prediction by capturing protein expression patterns linked to diverse pathological processes. Leveraging data from 2,923 proteins measured in 53,030 UK Biobank participants, we develo...

Modeling the prediction of spontaneous rupture and bleeding in hepatocellular carcinoma via machine learning algorithms.

Scientific reports
This study aimed to identify the risk factors associated with spontaneous rupture and bleeding in hepatocellular carcinoma, establish a prediction model for spontaneous rupture bleeding via a machine learning algorithm, and validate and evaluate the ...

Moral judgments in online discourse are not biased by gender.

Scientific reports
The interaction between social norms and gender roles prescribes gender-specific behaviors that influence moral judgments. While previous work has demonstrated the existence of gender-bias in judgments, these studies are mainly based on controlled ex...

Machine learning developed LKB1-AMPK signaling related signature for prognosis and drug sensitivity in hepatocellular carcinoma.

Scientific reports
Hepatocellular carcinoma (HCC) is one of the most common tumors worldwide, posing a significant threat to the life and health of people globally. LKB1-AMPK signaling pathway plays a significant role in the regulation of cellular metabolism, prolifera...

XAI-XGBoost: an innovative explainable intrusion detection approach for securing internet of medical things systems.

Scientific reports
The Internet of Medical Things (IoMT) has transformed healthcare delivery but faces critical challenges, including cybersecurity threats that endanger patient safety and data integrity. Intrusion Detection Systems (IDS) are essential for protecting I...

Sentiment classification for telugu using transformed based approaches on a multi-domain dataset.

Scientific reports
Sentiment analysis is an essential component of Natural Language Processing (NLP) in resource-abundant languages such as English. Nevertheless, poor-resource languages such as Telugu have experienced limited efforts owing to multiple considerations, ...