AIMC Topic: Humans

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deepAFT: A nonlinear accelerated failure time model with artificial neural network.

Statistics in medicine
The Cox regression model or accelerated failure time regression models are often used for describing the relationship between survival outcomes and potential explanatory variables. These models assume the studied covariates are connected to the survi...

Artificial intelligence for small molecule anticancer drug discovery.

Expert opinion on drug discovery
INTRODUCTION: The transition from conventional cytotoxic chemotherapy to targeted cancer therapy with small-molecule anticancer drugs has enhanced treatment outcomes. This approach, which now dominates cancer treatment, has its advantages. Despite th...

A new methodology for determining the central pressure waveform from peripheral measurement using Fourier-based machine learning.

Artificial intelligence in medicine
Radial applanation tonometry is a well-established technique for hemodynamic monitoring and is becoming popular in affordable non-invasive wearable healthcare electronics. To assess the central aortic pressure using radial-based measurements, there i...

AMFP-net: Adaptive multi-scale feature pyramid network for diagnosis of pneumoconiosis from chest X-ray images.

Artificial intelligence in medicine
Early detection of pneumoconiosis by routine health screening of workers in the mining industry is critical for preventing the progression of this incurable disease. Automated pneumoconiosis classification in chest X-ray images is challenging due to ...

EHR coding with hybrid attention and features propagation on disease knowledge graph.

Artificial intelligence in medicine
And sentences associated with these attributes and relationships have been neglected. in this paper ►We propose an end-to-end model called Knowledge Graph Enhanced neural network (KGENet) to address the above shortcomings. specifically ►We first cons...

Bio-inspired deep learning-personalized ensemble Alzheimer's diagnosis model for mental well-being.

SLAS technology
Most classification models for Alzheimer's Diagnosis (AD) do not have specific strategies for individual input samples, leading to the problem of easily overlooking personalized differences between samples. This research introduces a customized dynam...

Small sized centroblasts as poor prognostic factor in follicular lymphoma - Based on artificial intelligence analysis.

Computers in biology and medicine
Histological assessment of centroblasts is an important evaluation in the diagnosis of follicular lymphoma, but there is substantial observer variation in assessment among hematopathologists. We aimed to perform quantitative morphological analysis of...

Precision Drug Repurposing: A Deep Learning Toolkit for Identifying 34 Hyperpigmentation-Associated Genes and Optimizing Treatment Selection.

Annals of plastic surgery
BACKGROUND: Hyperpigmentation is a skin disorder characterized by a localized darkening of the skin due to increased melanin production. When patients fail first line topical treatments, secondary treatments such as chemical peels and lasers are offe...

Leveraging deep learning for detecting red blood cell morphological changes in blood films from children with severe malaria anaemia.

British journal of haematology
In sub-Saharan Africa, acute-onset severe malaria anaemia (SMA) is a critical challenge, particularly affecting children under five. The acute drop in haematocrit in SMA is thought to be driven by an increased phagocytotic pathological process in the...

Raman spectroscopy with an improved support vector machine for discrimination of thyroid and parathyroid tissues.

Journal of biophotonics
The objective of this study was to discriminate thyroid and parathyroid tissues using Raman spectroscopy combined with an improved support vector machine (SVM) algorithm. In thyroid surgery, there is a risk of inadvertently removing the parathyroid g...