AI Medical Compendium Journal:
Cell reports. Medicine

Showing 31 to 40 of 51 articles

Artificial intelligence in medicine: Overcoming or recapitulating structural challenges to improving patient care?

Cell reports. Medicine
There is considerable enthusiasm about the prospect that artificial intelligence (AI) will help to improve the safety and efficacy of health services and the efficiency of health systems. To realize this potential, however, AI systems will have to ov...

An imaging-based artificial intelligence model for non-invasive grading of hepatic venous pressure gradient in cirrhotic portal hypertension.

Cell reports. Medicine
The hepatic venous pressure gradient (HVPG) is the gold standard for cirrhotic portal hypertension (PHT), but it is invasive and specialized. Alternative non-invasive techniques are needed to assess the hepatic venous pressure gradient (HVPG). Here, ...

The inclusion of augmented intelligence in medicine: A framework for successful implementation.

Cell reports. Medicine
Artificial intelligence (AI) algorithms are being applied across a large spectrum of everyday life activities. The implementation of AI algorithms in clinical practice has been met with some skepticism and concern, mainly because of the uneasiness th...

Subtyping of mild cognitive impairment using a deep learning model based on brain atrophy patterns.

Cell reports. Medicine
Trajectories of cognitive decline vary considerably among individuals with mild cognitive impairment (MCI). To address this heterogeneity, subtyping approaches have been developed, with the objective of identifying more homogeneous subgroups. To date...

Supervised learning based on tumor imaging and biopsy transcriptomics predicts response of hepatocellular carcinoma to transarterial chemoembolization.

Cell reports. Medicine
Although transarterial chemoembolization (TACE) is the most widely used treatment for intermediate-stage, unresectable hepatocellular carcinoma (HCC), it is only effective in a subset of patients. In this study, we combine clinical, radiological, and...

Use of machine learning to identify a T cell response to SARS-CoV-2.

Cell reports. Medicine
The identification of SARS-CoV-2-specific T cell receptor (TCR) sequences is critical for understanding T cell responses to SARS-CoV-2. Accordingly, we reanalyze publicly available data from SARS-CoV-2-recovered patients who had low-severity disease ...

AI-powered integration of multimodal imaging in precision medicine for neuropsychiatric disorders.

Cell reports. Medicine
Neuropsychiatric disorders have complex pathological mechanism, pronounced clinical heterogeneity, and a prolonged preclinical phase, which presents a challenge for early diagnosis and development of precise intervention strategies. With the developm...

Machine learning-based analysis identifies and validates serum exosomal proteomic signatures for the diagnosis of colorectal cancer.

Cell reports. Medicine
The potential of serum extracellular vesicles (EVs) as non-invasive biomarkers for diagnosing colorectal cancer (CRC) remains elusive. We employed an in-depth 4D-DIA proteomics and machine learning (ML) pipeline to identify key proteins, PF4 and AACT...

Racism is an ethical issue for healthcare artificial intelligence.

Cell reports. Medicine
There is growing attention and evidence that healthcare AI is vulnerable to racial bias. Despite the renewed attention to racism in the United States, racism is often disconnected from the literature on ethical AI. Addressing racism as an ethical iss...

Artificial intelligence, ChatGPT, and other large language models for social determinants of health: Current state and future directions.

Cell reports. Medicine
This perspective highlights the importance of addressing social determinants of health (SDOH) in patient health outcomes and health inequity, a global problem exacerbated by the COVID-19 pandemic. We provide a broad discussion on current developments...