AIMC Topic: Humans

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Artificial intelligence for breast cancer analysis: Trends & directions.

Computers in biology and medicine
Breast cancer is one of the leading causes of death among women. Early detection of breast cancer can significantly improve the lives of millions of women across the globe. Given importance of finding solution/framework for early detection and diagno...

PanClassif: Improving pan cancer classification of single cell RNA-seq gene expression data using machine learning.

Genomics
Cancer is one of the major causes of human death per year. In recent years, cancer identification and classification using machine learning have gained momentum due to the availability of high throughput sequencing data. Using RNA-seq, cancer researc...

Surgical assistant manipulator with diagonal joints and multi-stage telescopic screws for laparoscopic solo surgery.

International journal of computer assisted radiology and surgery
PURPOSE: A surgeon in a sterilized area can perform robotically assisted laparoscopic solo surgery while controlling a laparoscope-holding robot for view stabilization and a forceps robot for pulling organs. At present, no locally operated surgical a...

Predicting liver cancers using skewed epidemiological data.

Artificial intelligence in medicine
Liver Cancer is a threat to human health and life over the world. The key to reduce liver cancer incidence is to identify high-risk populations and carry out individualized interventions before cancer occurrence. Building predictive models based on m...

Extendable and explainable deep learning for pan-cancer radiogenomics research.

Current opinion in chemical biology
Radiogenomics is a field where medical images and genomic profiles are jointly analyzed to answer critical clinical questions. Specifically, people want to identify non-invasive imaging biomarkers that are associated with both genomic features and cl...

Development of a deep learning-based method to diagnose pulmonary ground-glass nodules by sequential computed tomography imaging.

Thoracic cancer
BACKGROUND: Early identification of the malignant propensity of pulmonary ground-glass nodules (GGNs) can relieve the pressure from tracking lesions and personalized treatment adaptation. The purpose of this study was to develop a deep learning-based...

Thin-Slice Pituitary MRI with Deep Learning-Based Reconstruction for Preoperative Prediction of Cavernous Sinus Invasion by Pituitary Adenoma: A Prospective Study.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Accurate radiologic prediction of cavernous sinus invasion by pituitary adenoma remains challenging. We aimed to assess whether 1-mm-slice-thickness MRI with deep learning-based reconstruction can better predict cavernous sinu...

Reconstruction of three-dimensional tomographic patient models for radiation dose modulation in CT from two scout views using deep learning.

Medical physics
BACKGROUND: A tomographic patient model is essential for radiation dose modulation in x-ray computed tomography (CT). Currently, two-view scout images (also known as topograms) are used to estimate patient models with relatively uniform attenuation c...

Precipitate-Supported Thermal Proteome Profiling Coupled with Deep Learning for Comprehensive Screening of Drug Target Proteins.

ACS chemical biology
Although thermal proteome profiling (TPP) acts as a popular modification-free approach for drug target deconvolution, some key problems are still limiting screening sensitivity. In the prevailing TPP workflow, only the soluble fractions are analyzed ...

Interactive Deep Learning for Shelf Life Prediction of Muskmelons Based on an Active Learning Approach.

Sensors (Basel, Switzerland)
A pivotal topic in agriculture and food monitoring is the assessment of the quality and ripeness of agricultural products by using non-destructive testing techniques. Acoustic testing offers a rapid in situ analysis of the state of the agricultural g...