AIMC Topic: Female

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Improved patient identification by incorporating symptom severity in deep learning using neuroanatomic images in first episode schizophrenia.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
Brain alterations associated with illness severity in schizophrenia remain poorly understood. Establishing linkages between imaging biomarkers and symptom expression may enhance mechanistic understanding of acute psychotic illness. Constructing model...

Supporting the care to breast cancer patients with unique needs: Evidence from online community members' responses.

International journal of medical informatics
BACKGROUND: Breast cancer is the most common cancer diagnosed in women globally. Online cancer communities (OCCs) provide platforms for breast cancer patients to connect, share experiences, and support each other. These communities facilitate discuss...

Artificial Intelligence Compared to Manual Selection of Prospective Surgical Residents.

Journal of surgical education
BACKGROUND: Artificial Intelligence (AI) in the selection of residency program applicants is a new tool that is gaining traction, with the aim of screening high numbers of applicants while introducing objectivity and mitigating bias in a traditionall...

Bacterial profile-based body fluid identification using a machine learning approach.

Genes & genomics
BACKGROUND: Identifying the origins of biological traces is critical for the reconstruction of crime scenes in forensic investigations. Traditional methods for body fluid identification rely on chemical, enzymatic, immunological, and spectroscopic te...

Automated real-world data integration improves cancer outcome prediction.

Nature
The digitization of health records and growing availability of tumour DNA sequencing provide an opportunity to study the determinants of cancer outcomes with unprecedented richness. Patient data are often stored in unstructured text and siloed datase...

Feature Selection and Machine Learning Approaches in Prediction of Current E-Cigarette Use Among U.S. Adults in 2022.

International journal of environmental research and public health
Feature selection is essentially the process of picking informative and relevant features from a larger collection of features. Few studies have focused on predictors for current e-cigarette use among U.S. adults using feature selection and machine l...

Machine learning models in evaluating the malignancy risk of ovarian tumors: a comparative study.

Journal of ovarian research
OBJECTIVES: The study aimed to compare the diagnostic efficacy of the machine learning models with expert subjective assessment (SA) in assessing the malignancy risk of ovarian tumors using transvaginal ultrasound (TVUS).

Predictive modeling of preoperative acute heart failure in older adults with hypertension: a dual perspective of SHAP values and interaction analysis.

BMC medical informatics and decision making
BACKGROUND: In older adults with hypertension, hip fractures accompanied by preoperative acute heart failure significantly elevate surgical risks and adverse outcomes, necessitating timely identification and management to improve patient outcomes.

Computed tomography enterography radiomics and machine learning for identification of Crohn's disease.

BMC medical imaging
BACKGROUND: Crohn's disease is a severe chronic and relapsing inflammatory bowel disease. Although contrast-enhanced computed tomography enterography is commonly used to evaluate crohn's disease, its imaging findings are often nonspecific and can ove...

Random survival forest algorithm for risk stratification and survival prediction in gastric neuroendocrine neoplasms.

Scientific reports
This study aimed to construct and assess a machine-learning algorithm designed to forecast survival rates and risk stratification for patients with gastric neuroendocrine neoplasms (gNENs) after diagnosis. Data on patients with gNENs were extracted a...