AI in medicine

In recent years, researchers have successfully recognised human activities using commercially available WiFi (Wireless Fidelity) devices. The channel state information (CSI) can be gathered at the access point with the help of a network interface controller (NIC card). These CSI streams are sensitive to human body motions and produce abrupt changes (fluctuations) in their magnitude and phase values when a moving object interacts with a transmitter and receiver pair. This sensing methodology is gaining popularity compared to traditional approaches involving wearable technology, as it is a contactless sensing strategy with no cumbersome sensing equipments fitted on the target with preserved privacy since no personal information of the subject is collected...

The paper presents an innovative computational framework for predictive solutions for simulating the spread of malaria. The structure incorporates sophisticated computing methods to improve the reliability of predicting malaria outbreaks. The study strives to provide a strong and effective tool for forecasting the propagation of malaria via the use of an AI-based recurrent neural network (RNN). The model is classified into two groups, consisting of humans and mosquitoes. To develop the model, the traditional Ross-Macdonald model is expanded upon, allowing for a more comprehensive analysis of the intricate dynamics at play...

No abstract text is available yet for this article.

BACKGROUND: Given the advances in medicine, women with Fontan circulation are now reaching childbearing age. However, data on the mode of delivery and anesthetic management of these patients are limited. We report the cases of five pregnant women with Fontan circulation. CASE PRESENTATION: The mean age at delivery was 28 ± 3 years, and the mean gestational period was 34 weeks and 3 days. Anticoagulation therapy was switched from warfarin and aspirin to continuous intravenous heparin...

The novel metal(II)-based complexes HA-Cu, HA-Co, and HA-Ni with phenanthroline, sulfamethazine, and aromatic-aromatic coupled disulfamethazines as ligands were synthesized and characterized. HA-Cu, HA-Co, and HA-Ni all showed a broad spectrum of cytotoxicity and antiangiogenesis. HA-Cu was superior to HA-Co and HA-Ni, and even superior to DDP, showing significant inhibitory effect on the growth and development of tripe-negative breast cancer in vivo and in vitro. HA-Cu exhibited observable synergistic effects of antiproliferation, antiangiogenesis, anti-inflammatory, pro-apoptosis, and cuproptosis to effectively inhibited tumor survival and development...

BACKGROUND: Malformations of cortical development (MCD) are a group of congenital disorders characterized by structural abnormalities in the brain cortex. The clinical manifestations include refractory epilepsy, mental retardation, and cognitive impairment. Genetic factors play a key role in the etiology of MCD. Currently, there is no curative treatment for MCD. Phenotypes such as epilepsy and cerebral palsy cannot be observed in the fetus. Therefore, the diagnosis of MCD is typically based on fetal brain magnetic resonance imaging (MRI), ultrasound, or genetic testing...

Critical care medicine in the 21st century has witnessed remarkable advancements that have significantly improved patient outcomes in intensive care units (ICUs). This abstract provides a concise summary of the latest developments in critical care, highlighting key areas of innovation. Recent advancements in critical care include Precision Medicine: Tailoring treatments based on individual patient characteristics, genomics, and biomarkers to enhance the effectiveness of therapies. The objective is to describe the recent advancements in Critical Care Medicine...

OBJECTIVE: To compare vaccination willingness before rollout and 1 year post-rollout uptake among the general population and under-resourced communities in high-income countries. DESIGN: A realist review. DATA SOURCES: Embase, PubMed, Dimensions ai and Google Scholar. SETTING: High-income countries. DEFINITIONS: We defined vaccination willingness as the proportion of participants willing or intending to receive vaccines prior to availability...

PURPOSE: Further acceleration of DWI in diagnostic radiology is desired but challenging mainly due to low SNR in high b-value images and associated bias in quantitative ADC values. Deep learning-based reconstruction and denoising may provide a solution to address this challenge. METHODS: The effects of SNR reduction on ADC bias and variability were investigated using a commercial diffusion phantom and numerical simulations. In the phantom, performance of different reconstruction methods, including conventional parallel (SENSE) imaging, compressed sensing (C-SENSE), and compressed SENSE acceleration with an artificial intelligence deep learning-based technique (C-SENSE AI), was compared at different acceleration factors and flip angles using ROI-based analysis...

PET scans provide additional clinical value but are costly and not universally accessible. Salehjahromi et al.1 developed an AI-based pipeline to synthesize PET images from diagnostic CT scans, demonstrating its potential clinical utility across various clinical tasks for lung cancer.

Filariasis, a neglected tropical disease caused by roundworms, is a significant public health concern in many tropical countries. Microscopic examination of blood samples can detect and differentiate parasite species, but it is time consuming and requires expert microscopists, a resource that is not always available. In this context, artificial intelligence (AI) can assist in the diagnosis of this disease by automatically detecting and differentiating microfilariae. In line with the target product profile for lymphatic filariasis as defined by the World Health Organization, we developed an edge AI system running on a smartphone whose camera is aligned with the ocular of an optical microscope that detects and differentiates filarias species in real time without the internet connection...

OBJECTIVE: To support a diverse sample of Australians to make recommendations about the use of artificial intelligence (AI) technology in health care. STUDY DESIGN: Citizens' jury, deliberating the question: "Under which circumstances, if any, should artificial intelligence be used in Australian health systems to detect or diagnose disease?" SETTING, PARTICIPANTS: Thirty Australian adults recruited by Sortition Foundation using random invitation and stratified selection to reflect population proportions by gender, age, ancestry, highest level of education, and residential location (state/territory; urban, regional, rural)...

Background and objectives: As microbes are developing resistance to antibiotics, natural, botanical drugs or traditional herbal medicine are presently being studied with an eye of great curiosity and hope. Hence, complementary and alternative treatments for uncomplicated pelvic inflammatory disease (uPID) are explored for their efficacy. Therefore, this study determined the therapeutic efficacy and safety of Sesamum indicum Linn seeds with Rosa damascena Mill Oil in uPID with standard control. Additionally, we analyzed the data with machine learning...

Integrating healthcare into traffic accident prevention through predictive modeling holds immense potential. Decentralized Defense presents a transformative vision for combating cyberbullying, prioritizing user privacy, fostering a safer online environment, and offering valuable insights for both healthcare and predictive modeling applications. As cyberbullying proliferates in social media, a pressing need exists for a robust and innovative solution that ensures user safety in the cyberspace. This paper aims toward introducing the approach of merging Blockchain and Federated Learning (FL), to create a decentralized AI solutions for cyberbullying...

No abstract text is available yet for this article.

Building trustworthy and transparent image-based medical artificial intelligence (AI) systems requires the ability to interrogate data and models at all stages of the development pipeline, from training models to post-deployment monitoring. Ideally, the data and associated AI systems could be described using terms already familiar to physicians, but this requires medical datasets densely annotated with semantically meaningful concepts. In the present study, we present a foundation model approach, named MONET (medical concept retriever), which learns how to connect medical images with text and densely scores images on concept presence to enable important tasks in medical AI development and deployment such as data auditing, model auditing and model interpretation...

Internet finance has permeated into myriad households, bringing about lifestyle convenience alongside potential risks. Presently, internet finance enterprises are progressively adopting machine learning and other artificial intelligence methods for risk alertness. What is the current status of the application of various machine learning models and algorithms across different institutions? Is there an optimal machine learning algorithm suited for the majority of internet finance platforms and application scenarios? Scholars have embarked on a series of studies addressing these questions; however, the focus predominantly lies in comparing different algorithms within specific platforms and contexts, lacking a comprehensive discourse and summary on the utilization of machine learning in this domain...

This study assesses the status of outcome measures in the randomized controlled trial(RCT) involving the kidney-tonif-ying and blood-activating method for treating knee osteoarthritis(KOA), aiming to establish a theoretical foundation for the development of a core set of outcome measures in traditional Chinese medicine(TCM) treatment of KOA. The relevant articles were retrieved from CNKI, Wanfang, VIP, SinoMed, PubMed, EMbase, Cochrane Library, and Web of Science, in addition to ClinicalTrials.gov and the China Clinical Trial Registration Center, with the time interval from inception to August 2023...

As a common medicinal and edible resource in China, Coicis Semen has a long history of cultivation and medicinal use. Traditional Chinese medicine(TCM) clinically believes that Coicis Semen has the effect of strengthening the spleen and tonifying the lungs, clearing heat and dampness, removing pus and paralysis, and stopping diarrhea. Therefore, it is used to treat edema, foot odor, spleen deficiency, diarrhea, and other symptoms. The above effects are closely related to the active ingredients of Coicis Semen, such as esters, fatty acids, polysaccharides, proteins, as well as phenolic acids, sterols, flavonoids, lactams, triterpenes, alkaloids, and adenosine...

This study systematically collected, analyzed, and evaluated randomized controlled trial(RCT) in the treatment of diabetic foot ulcer(DFU). The aim as provide references for future studies and to enhance the application of clinical evidence. The RCT of DFU treated with Chinese Patent Medicine was obtained and analyzed using the AI-Clinical Evidence Database of Chinese Patent Medicine(AICED-CPM). The analysis was supplemented with data from CNKI, Wanfang, VIP, SinoMed, PubMed, EMbase, Cochrane Library, and Web of Science...