AIMC Topic: Female

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Leveraging diverse cell-death patterns in diagnosis of sepsis by integrating bioinformatics and machine learning.

PeerJ
BACKGROUND: Sepsis is a life-threatening disease causing millions of deaths every year. It has been reported that programmed cell death (PCD) plays a critical role in the development and progression of sepsis, which has the potential to be a diagnosi...

Machine learning-based prediction of distant metastasis risk in invasive ductal carcinoma of the breast.

PloS one
More than 90% of deaths due to breast cancer (BC) are due to metastasis-related complications, with invasive ductal carcinoma (IDC) of the breast being the most common pathologic type of breast cancer and highly susceptible to metastasis to distant o...

Artificial Intelligence Algorithms, Bias, and Innovation: Implications for Social Work.

Journal of evidence-based social work (2019)
PURPOSE: Artificial Intelligence (AI) technologies are rapidly expanding across diverse contexts. As the reach of AI continues to grow, there is a need to examine student perspectives on the increasing prevalence of AI and AI-based practice approache...

Is personality associated with the lived experience of the NHS England low calorie diet programme: A pilot study.

Clinical obesity
This pilot study explored the use of a novel behavioural artificial intelligence (AI) tool to examine whether personality is associated with the lived experience of the NHS England launched a low calorie diet (LCD). A cross-sectional survey was disse...

Development and evaluation of a multivariable prediction model for overall survival in advanced stage pulmonary carcinoid using machine learning.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
BACKGROUND: Evidence is limited on whether patients with advanced pulmonary carcinoid (APC) benefit from comprehensive pulmonary resection (CPR), chemotherapy, or radiotherapy. Existing prognostic models for APC are limited and do not guide treatment...

Identification and taste presentation characteristics of umami peptides from soybean paste based on peptidomics and virtual screening.

Food chemistry
This research concentrated on soybean paste fermented with Tetragenococcus halophilus, employing peptidomics and machine learning methodologies to screen for novel umami peptides. Taste characteristics of umami peptides were evaluated through sensory...

Non-invasive classification of non-neoplastic and neoplastic gallbladder polyps based on clinical imaging and ultrasound radiomics features: An interpretable machine learning model.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
BACKGROUND: Gallbladder (GB) adenomas, precancerous lesions for gallbladder carcinoma (GBC), lack reliable non-invasive tools for preoperative differentiation of neoplastic polyps from cholesterol polyps. This study aimed to evaluate an interpretable...

Finding purpose: Integrated latent profile and machine learning analyses identify purpose in life as an important predictor of high-functioning recovery after alcohol treatment.

Addictive behaviors
BACKGROUND: Recent investigations of recovery from alcohol use disorder (AUD) have distinguished subgroups of high and low functioning recovery in data from randomized controlled trials of behavioral treatments for AUD. Analyses considered various in...

The predictive role of sedentary behavior and physical activity on adolescent depressive symptoms: A machine learning approach.

Journal of affective disorders
OBJECTIVE: This study aims to investigate the predictive value of sedentary behavior and physical activity in adolescent depressive symptoms.