Artificial intelligence (AI), particularly deep learning, has demonstrated remarkable performance in medical imaging across a variety of modalities, including X-ray, computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, positron emission tomography (PET), and pathological imaging. However, most existing state-of-the-art AI techniques are task-specific and focus on a limited range of imaging modalities. Compared to these task-specific models, emerging foundation models represent a significant milestone in AI development. These models can learn generalized representations of medical images and apply them to downstream tasks through zero-shot or few-shot fine-tuning. Foundation models have the potential to address the comprehensive and multifactorial challenges encountered in clinical practice. This article reviews the clinical applications of both task-specific and foundation models, highlighting their differences, complementarities, and clinical relevance. We also examine their future research directions and potential challenges. Unlike the replacement relationship seen between deep learning and traditional machine learning, task-specific and foundation models are complementary, despite inherent differences. While foundation models primarily focus on segmentation and classification, task-specific models are integrated into nearly all medical image analyses. However, with further advancements, foundation models could be applied to other clinical scenarios. In conclusion, all indications suggest that task-specific and foundation models, especially the latter, have the potential to drive breakthroughs in medical imaging, from image processing to clinical workflows.
Humans ; Artificial Intelligence ; Deep Learning ; Diagnostic Imaging/methods* ; Magnetic Resonance Imaging ; Tomography, X-Ray Computed ; Positron-Emission Tomography

OBJECTIVES: To develop a Chinese version of the Long-Term Conditions Questionnaire (LTCQ) and to test its reliability and validity in Chinese patients with chronic diseases. METHODS: With the consent of the original authors, a Chinese version of LTCQ was developed according to the cultural adjustment guidelines. A questionnaire survey was conducted on 319 patients with chronic diseases in Sir Run Run Shaw Hospital, Wuyi County First People's Hospital and Hangzhou Gongchen Bridge Street Health Service Center. The questionnaire was evaluated by item analysis (including frequency analysis, total question correlation method and critical ratio method), reliability analysis (Cronbach's alpha coefficient) and validity analysis [including content validity (expert scoring method) and structural validity (exploratory factor analysis)]. RESULTS The Chinese version of the LTCQ included 20 entries, with a Cronbach's alpha coefficient of 0.926, a retest reliability of 0.829, a split-half reliability of 0.878, an entry content validity index of 1, and a content validity index at the questionnaire level of 1. Four common factors were extracted by exploratory factor analysis, namely physical state and daily life, psychological state, support and coping, and safe environment, with a cumulative variance contribution rate of 67.244%. Discussion: The Chinese version of the LTCQ developed in this study has good reliability and validity and it may be used to assess the long-term conditions of patients with chronic diseases in China.
Humans ; Asian People ; China ; Chronic Disease ; Quality of Life ; Reproducibility of Results ; Surveys and Questionnaires

Objective To explore the risk factors of sepsis complicated with hepatic insufficiency in elder patients.Methods With retrospective case-control study method,according to whether or not complicated with hepatic insufficiency,a total of 384 elder sepsis patients were divided into case group (91 patients) and control group(293 patients),then single factor analysis and multiple factors Logistic regression methods were used to screen the risk factors.Results Single factor analysis identified 6 kinds of significant variables,including age(P =0.000),history of alcohol(P =0.006),chronic diseases(P =0.001),arterial blood lactate level (P =0.035),mechanical ventilation (P =0.009) and acute physiology and chronic health evaluation Ⅲ score (APACHE-Ⅲ) scores(P =0.004).Multiple factors Logistic regression analysis showed that age,history of alcohol,chronic diseases,arterial blood lactate level,mechanical ventilation,APACHE-Ⅲ scores were correlated with sepsis complicated hepatic insuffciency in elder patients (P ＜ 0.01 or ＜ 0.05).Conclusion The risk factors which closely relate to sepsis complicated with hepatic insufficiency in elder patients are age,history of alcohol,chronic diseases,arterial blood lactate level,mechanical ventilation,APACHE-Ⅲ scores.

Objective To detect the proteus and analyze the drug-resistance in intensive care unit.Methods From Jan 2005 to Dec 2006,proteus was detected by Disc diffusion test(K-B method)to study the antimicrobial resistance in ICU and general ward,and compared the drug-resistance.Results The isolating rate of proteus was 80.9% in sputum,and proteus mirabilis accouted for 80.4%.The resistance rates to ciprofloxacin,amikacin,cefotaxim,ceftazidime,cefmetazole and piperacillin/Tazobactam were between 64%~77%,and 32%~41% in imipenem and cefoperazone/sulbactam.Compared with general ward,the antibiotic resistant rate existed significant difference.And the antibiotic resistant rate of other type proteus had significant difference between ICU and general ward.Conclusion Properly detecting Proteus in time is imporrant to use antibiotic and to avoid nosocomial outbreak infections by Proteus.