AIMC Topic: Humans

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Preoperative prediction of lymph node status in patients with colorectal cancer. Developing a predictive model using machine learning.

International journal of colorectal disease
PURPOSE: Develop a prediction model to determine the probability of no lymph node metastasis (pN0) in patients with colorectal cancer.

CNN and SVM-Based Models for the Detection of Heart Failure Using Electrocardiogram Signals.

Sensors (Basel, Switzerland)
Heart failure (HF) is a serious condition in which the heart fails to supply the body with enough oxygen and nutrients to function normally. Early and accurate detection of heart failure is critical for impeding disease progression. An electrocardiog...

High-confidence cancer patient stratification through multiomics investigation of DNA repair disorders.

Cell death & disease
Multiple cancer types have limited targeted therapeutic options, in part due to incomplete understanding of the molecular processes underlying tumorigenesis and significant intra- and inter-tumor heterogeneity. Identification of novel molecular bioma...

Development of a Novel Deep Learning-Based Prediction Model for the Prognosis of Operable Cervical Cancer.

Computational and mathematical methods in medicine
BACKGROUND: Cervical cancer ranks as the 4th most common female cancer worldwide. Early stage cervical cancer patients can be treated with operation, but clinical staging system is not a good predictor of patients' survival. We aimed to develop a nov...

Preliminary outcomes of kinematically aligned robot-assisted total knee arthroplasty with patient-specific cartilage thickness measurement.

Journal of robotic surgery
This study aimed to assess the preliminary outcomes of kinematically aligned robot-assisted total knee arthroplasty (TKA) with patient-specific cartilage thickness measurement. Patients who underwent kinematically aligned robot-assisted TKA were incl...

Artificial intelligence assistance for women who had spot compression view: reducing recall rates for digital mammography.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Mammography yields inevitable recall for indeterminate findings that need to be confirmed with additional views.

Predicting muscle invasion in bladder cancer by deep learning analysis of MRI: comparison with vesical imaging-reporting and data system.

European radiology
OBJECTIVES: To compare the diagnostic performance of a novel deep learning (DL) method based on T2-weighted imaging with the vesical imaging-reporting and data system (VI-RADS) in predicting muscle invasion in bladder cancer (MIBC).

Uncertainty-aware physics-driven deep learning network for free-breathing liver fat and R * quantification using self-gated stack-of-radial MRI.

Magnetic resonance in medicine
PURPOSE: To develop a deep learning-based method for rapid liver proton-density fat fraction (PDFF) and R * quantification with built-in uncertainty estimation using self-gated free-breathing stack-of-radial MRI.

Deep learning-based internal gross target volume definition in 4D CT images of lung cancer patients.

Medical physics
BACKGROUND: Contouring of internal gross target volume (iGTV) is an essential part of treatment planning in radiotherapy to mitigate the impact of intra-fractional target motion. However, it is usually time-consuming and easily subjected to intra-obs...

A cable-driven highly compact single port laparoscopic surgical robot with sequentially inserted arms.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: The single port surgical robot causes only one incision and brings many benefits to patients. It is very challenging to design a single port surgical robot that causes a smaller incision than current products.