AIMC Topic: Adult

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Artificial intelligence measured 3D body composition to predict pathological response in rectal cancer patients.

ANZ journal of surgery
BACKGROUND: The treatment of locally advanced rectal cancer (LARC) is moving towards total neoadjuvant therapy and potential organ preservation. Of particular interest are predictors of pathological complete response (pCR) that can guide personalized...

Development and external validation of a machine learning model for prediction of survival in extremity leiomyosarcoma.

Surgical oncology
PURPOSE: Machine learning (ML) models have been used to predict cancer survival in several sarcoma subtypes. However, none have investigated extremity leiomyosarcoma (LMS). ML is a powerful tool that has the potential to better prognosticate extremit...

Perspective analysis of assistive robots for elderly in India.

Disability and rehabilitation. Assistive technology
PURPOSE: Assistive technology for elderly are advancing, and this study aimed to analyse the Indian perspective on utilising assistive robot technology for aiding elderly individuals.

Prediction of extraction difficulty for impacted maxillary third molars with deep learning approach.

Journal of stomatology, oral and maxillofacial surgery
OBJECTIVE: The aim of this study is to determine if a deep learning (DL) model can predict the surgical difficulty for impacted maxillary third molar tooth using panoramic images before surgery.

Machine-Learning and Radiomics-Based Preoperative Prediction of Ki-67 Expression in Glioma Using MRI Data.

Academic radiology
BACKGROUND: Gliomas are the most common primary brain tumours and constitute approximately half of all malignant glioblastomas. Unfortunately, patients diagnosed with malignant glioblastomas typically survive for less than a year. In light of this ci...

Differentiation of testicular seminomas from nonseminomas based on multiphase CT radiomics combined with machine learning: A multicenter study.

European journal of radiology
BACKGROUND: Differentiating seminomas from nonseminomas is crucial for formulating optimal treatment strategies for testicular germ cell tumors (TGCTs). Therefore, our study aimed to develop and validate a clinical-radiomics model for this purpose.

Development of a multi-wear-site, deep learning-based physical activity intensity classification algorithm using raw acceleration data.

PloS one
BACKGROUND: Accelerometers are widely adopted in research and consumer devices as a tool to measure physical activity. However, existing algorithms used to estimate activity intensity are wear-site-specific. Non-compliance to wear instructions may le...

A Machine Learning Model for Week-Ahead Hypoglycemia Prediction From Continuous Glucose Monitoring Data.

Journal of diabetes science and technology
BACKGROUND: Remote patient monitoring (RPM) programs augment type 1 diabetes (T1D) care based on retrospective continuous glucose monitoring (CGM) data. Few methods are available to estimate the likelihood of a patient experiencing clinically signifi...

Application of deep-learning to the automatic segmentation and classification of lateral lymph nodes on ultrasound images of papillary thyroid carcinoma.

Asian journal of surgery
PURPOSE: It is crucial to preoperatively diagnose lateral cervical lymph node (LN) metastases (LNMs) in papillary thyroid carcinoma (PTC) patients. This study aims to develop deep-learning models for the automatic segmentation and classification of L...

Prediction of acute methanol poisoning prognosis using machine learning techniques.

Toxicology
Methanol poisoning is a global public health concern, especially prevalent in developing nations. This study focuses on predicting the severity of methanol intoxication using machine learning techniques, aiming to improve early identification and pro...