AIMC Topic: Female

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CT-Based Deep Learning Predicts Prognosis in Esophageal Squamous Cell Cancer Patients Receiving Immunotherapy Combined with Chemotherapy.

Academic radiology
RATIONALE AND OBJECTIVES: Immunotherapy combined with chemotherapy has improved outcomes for some esophageal squamous cell carcinoma (ESCC) patients, but accurate pre-treatment risk stratification remains a critical gap. This study constructed a deep...

Diagnosis of Thyroid Nodule Malignancy Using Peritumoral Region and Artificial Intelligence: Results of Hand-Crafted, Deep Radiomics Features and Radiologists' Assessment in Multicenter Cohorts.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVE: To develop, test, and externally validate a hybrid artificial intelligence (AI) model based on hand-crafted and deep radiomics features extracted from B-mode ultrasound images in differentiating benign and malignant thyroid nodules compare...

Towards clinical prediction with transparency: An explainable AI approach to survival modelling in residential aged care.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Scalable, flexible and highly interpretable tools for predicting mortality in residential aged care facilities for the purpose of informing and optimizing palliative care decisions, do not exist. This study is the first and ...

Coupling analysis of diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) with abnormal cerebral blood flow in methamphetamine-dependent patients and its application in machine-learning-based classification.

Journal of affective disorders
BACKGROUND: Diffusion tensor imaging (DTI) analysis along the perivascular space (ALPS) index is currently widely employed to evaluate the neurophysiological activity in various neuropsychiatric disorders. However, there remains a scarcity of studies...

Breaking barriers: noninvasive AI model for BRAF mutation identification.

International journal of computer assisted radiology and surgery
OBJECTIVE: BRAF is the most common mutation found in thyroid cancer and is particularly associated with papillary thyroid carcinoma (PTC). Currently, genetic mutation detection relies on invasive procedures. This study aimed to extract radiomic featu...

Machine-learning tool for classifying pulmonary hypertension via expert reader-provided CT features: An educational resource for non-dedicated radiologists.

European journal of radiology
PURPOSE: Pulmonary hypertension (PH) is a complex disease classified into five groups (I-V) by the European Society of Cardiology/European Respiratory Society (ESC/ERS) guidelines. Chest contrast-enhanced computed tomography (CECT) is crucial in the ...

Sensory-biased autoencoder enables prediction of texture perception from food rheology.

Food research international (Ottawa, Ont.)
Understanding how the physical properties of food affect sensory perception remains a critical challenge for food design. Here, we present an innovative machine learning strategy to decode the complex relationships between non-Newtonian rheological a...

Enhanced heart failure mortality prediction through model-independent hybrid feature selection and explainable machine learning.

Journal of biomedical informatics
Heart failure (HF) remains a significant public health challenge with high mortality rates. Machine learning (ML) techniques offer a promising approach to predict HF mortality, potentially improving clinical outcomes. However, the effectiveness of th...

An Artificial Intelligence Model for Sensing Affective Valence and Arousal from Facial Images.

Sensors (Basel, Switzerland)
Artificial intelligence (AI) models can sense subjective affective states from facial images. Although recent psychological studies have indicated that dimensional affective states of valence and arousal are systematically associated with facial expr...