AIMC Topic: Machine Learning

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Options for postoperative radiation therapy in patients with de novo metastatic breast cancer.

Breast (Edinburgh, Scotland)
BACKGROUND: Although meta-analyses have demonstrated survival benefits associated with primary tumor resection in MBC, guidelines lack consensus on the survival benefit of postoperative radiation therapy (RT).

Exploring species taxonomic kingdom using information entropy and nucleotide compositional features of coding sequences based on machine learning methods.

Methods (San Diego, Calif.)
The flow of genetic information from DNA to protein is governed by the central dogma of molecular biology. Genetic drift and mutations usually lead to changes in DNA composition, thereby affecting the coding sequences (CDS) that encode functional pro...

Pancreas rejection: quieting the storm to preserve graft function.

Current opinion in organ transplantation
PURPOSE OF REVIEW: Allograft rejection remains enigmatic and elusive following pancreas transplantation. In the absence of early technical pancreas graft failure, pancreas allograft rejection is the major cause of death-censored pancreas graft loss b...

Decoding of lexical items and grammatical features in EEG: A cross-linguistic study.

Neuropsychologia
Diverse evidence supports the theory that bilingual language users have language-invariant representations of concepts and grammatical forms such as argument structure. Here we extend that work to test the representation of morphosyntactic features a...

Precision Strike Strategy for Liver Diseases Trilogy with Xiao-Chai-Hu Decoction: A Meta-Analysis with Machine Learning.

Phytomedicine : international journal of phytotherapy and phytopharmacology
BACKGROUND AND PURPOSE: The progression from hepatitis to liver fibrosis (LF) and ultimately to hepatic carcinoma (HCC) represents the advanced stages of various liver diseases. Currently, no universal treatment effectively addresses all three condit...

Development and validation of an interpretable machine learning model for diagnosing pathologic complete response in breast cancer.

Computer methods and programs in biomedicine
BACKGROUND: Pathologic complete response (pCR) following neoadjuvant chemotherapy (NACT) is a critical prognostic marker for patients with breast cancer, potentially allowing surgery omission. However, noninvasive and accurate pCR diagnosis remains a...

Facial surgery preview based on the orthognathic treatment prediction.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Orthognathic surgery consultations are essential for helping patients understand how their facial appearance may change after surgery. However, current visualization methods are often inefficient and inaccurate due to limite...

Predictive Analysis of Amyotrophic Lateral Sclerosis Progression and Mortality in a Clinic Cohort From Singapore.

Muscle & nerve
INTRODUCTION: There is currently no comprehensive Amyotrophic Lateral Sclerosis (ALS) patient database in Singapore comparable to those available in Europe and the United States. We established the Singapore ALS registry (SingALS) to draw meaningful ...

Birth weight prediction using artificial intelligence-based placental assessment from macroscopic photo: a retrospective study.

Placenta
BACKGROUND: This study aimed to predict newborn birth weight through multifactorial analysis of macroscopic placental images using artificial intelligence (AI).

GDM-BC: Non-invasive body composition dataset for intelligent prediction of Gestational Diabetes Mellitus.

Computers in biology and medicine
Gestational Diabetes Mellitus (GDM) refers to any degree of impaired glucose tolerance with onset or first recognition during pregnancy. As a high-prevalence disease, GDM damages the health of both pregnant women and fetuses in the short and long ter...