AI Clinics on Mobile (AICOM): Universal AI Doctors for the Underserved and Hard-to-Reach

This paper introduces Artificial Intelligence Clinics on Mobile (AICOM), an open-source project devoted to answering the United Nations Sustainable Development Goal 3 (SDG3) on health, which represents a universal recognition that health is fundamental to human capital and social and economic development. The core motivation for the AICOM project is the fact that over 80% of the people in the least developed countries (LDCs) own a mobile phone, even though less than 40% of these people have internet access. Hence, through enabling AI-based disease diagnostics and screening capability on affordable mobile phones without connectivity will be a critical first step to addressing healthcare access problems. The technologies developed in the AICOM project achieve exactly this goal, and we have demonstrated the effectiveness of AICOM on monkeypox screening tasks. We plan to continue expanding and open-sourcing the AICOM platform, aiming for it to evolve into an universal AI doctor for the Underserved and Hard-to-Reach

Automatic Segmentation and Measurement on Knee Computerized Tomography Images for Patellar Dislocation Diagnosis

Traditionally, for diagnosing patellar dislocation, clinicians make manual geometric measurements on computerized tomography (CT) images taken in the knee area, which is often complex and error-prone. Therefore, we develop a prototype CAD system for automatic measurement and diagnosis. We firstly segment the patella and the femur regions on the CT images and then measure two geometric quantities, patellar tilt angle (PTA), and patellar lateral shift (PLS) automatically on the segmentation results, which are finally used to assist in diagnoses. The proposed quantities are proved valid and the proposed algorithms are proved effective by experiments

Designing mesostructured iron (II) fluorides with a stable in situ polymer electrolyte interface for high-energy-density lithium-ion batteries

As high-energy cathode materials, conversion-type metal fluorides provide a prospective pathway for developing next-generation lithium-ion batteries. However, they suffer from severe performance decay owing to continuous structural destruction and active material dissolution upon cycling, which worsen at elevated temperatures. Here, we design a novel FeF2 cathode with in situ polymerized solid-state electrolyte systems to enhance the cycling ability of metal fluorides at 60 ​°C. Novel FeF2 with a mesoporous structure (meso-FeF2) improves Li+ diffusion and relieves the volume change that typically occurs during the alternating conversion reactions. The structural stability of the meso-FeF2 cathode is strengthened by an in situ polymerized solid-state electrolyte, which prevents the pulverization and ion dissolution that are inevitable for conventional liquid electrolytes. Under the double action of this in situ polymerized solid-state electrolyte and the meso-FeF2's mesoporous structure, the active material maintains an intact SEI layer and part of the mesoporous structure after long charge–discharge cycling, showing excellent cycling stability at high temperatures

Significant reduction of antibiotic consumption and patients' costs after an action plan in China, 2010-2014.

On July 1, 2011, the Chinese government launched a national Action Plan for antibiotic stewardship targeting antibiotic misuse in public hospitals. The aim of this study was to evaluate the impacts of the Action Plan in terms of frequency and intensity of antibiotic utilization and patients costs in public general hospitals.Administrative pharmacy data from July 2010 to June 2014 were sampled from 65 public general hospitals and divided into three segments: (1) July 2010 to June 2011 as the preparation period; (2) July 2011 to June 2012 as the intervention period; and (3) July 2012 to June 2014 as the assessment period. The outcome measures included (1) antibiotic prescribing rates; (2) intensity of antibiotic consumption; (3) patients costs; and (4) duration of peri-operative antibiotic treatment in clean surgeries of thyroidectomy, breast, hernia, and orthopedic procedures. Longitudinal and cross-sectional analyses were conducted.Longitudinal analyses showed significant trend changes in the frequency and intensity of antibiotic consumption, the patients' costs on antibiotics, and the duration of antibiotic treatment received by surgical patients undergoing the 4 clean procedures during the intervention period. Cross-sectional analyses showed that the antibiotic prescribing rates were reduced to 35.3% and 12.9% in inpatient and outpatient settings, that the intensity of antibiotic consumption was reduced to 35.9 DDD/100 bed-days, that patients' costs on antibiotics were reduced significantly, and that the duration of peri-operative antibiotic treatment received by surgical patients undergoing the 4 types of clean procedures decreased to less than 24 hour during the assessment period.The Action Plan, as a combination of managerial and professional strategies, was effective in reducing the frequency and intensity of antibiotic consumption, patients' costs on antibiotics, and the duration of peri-operative antibiotic treatment in the 4 clean surgeries

Changes in patients’ costs.

<p>The stack plots represent the average monthly data of costs for inpatients (A) and outpatients (B) during the preparation, intervention, and assessment periods. The costs are summarized as the costs on hospital stay (TO), medication (ME), antibiotics (AN), and very-restricted antibiotics (VR). Cross-sectional analyses were conducted by comparing the average yearly data on patents’ costs on hospital stay, medication, antibiotics, and very-restricted antibiotics (Very-Restricted) for both inpatients (C—F) and outpatients (G—I). P: preparation; I: intervention; A: assessment; *significant difference in intervention/assessment vs. preparation; ^#significant difference in assessment vs. intervention.</p

Changes in patients’ costs.

<p>The stack plots represent the average monthly data of costs for inpatients (A) and outpatients (B) during the preparation, intervention, and assessment periods. The costs are summarized as the costs on hospital stay (TO), medication (ME), antibiotics (AN), and very-restricted antibiotics (VR). Cross-sectional analyses were conducted by comparing the average yearly data on patents’ costs on hospital stay, medication, antibiotics, and very-restricted antibiotics (Very-Restricted) for both inpatients (C—F) and outpatients (G—I). P: preparation; I: intervention; A: assessment; *significant difference in intervention/assessment vs. preparation; ^#significant difference in assessment vs. intervention.</p

Regression analyses of ITS on the changes in antibiotic consumption.

<p>Changes in level and slope in antibiotic prescribing rates in inpatient (RATE_I), outpatient (RATE_O) and emergency (RATE_E) settings in the 65 general hospitals were analyzed using segmented regression analysis of ITS. The intensity of antibiotic consumption was expressed as DDD/100 bed-days for inpatient settings (DDD_I) or DDD/1000 outpatient-days for outpatient settings (DDD_O). The parameters of β1 to β5, expressed as Mean (SE), were described in the Methods.</p><p>*<i>p</i> < 0.05;</p><p>**<i>p</i> < 0.01;</p><p>***<i>p</i> < 0.001.</p><p>Regression analyses of ITS on the changes in antibiotic consumption.</p

Changes in antibiotic prescribing rates and intensity of antibiotic consumption.

<p>Time series of average monthly value of the antibiotic prescribing rates (A) were plotted for inpatient (IN), outpatient (OUT), and emergency (EM) settings. The data on intensity of antibiotic consumption were plotted for the inpatient (B) and outpatient settings (C). Cross-sectional analyses were conducted by comparing the average yearly data on antibiotic prescribing rates in inpatient (D), outpatient (E) and emergency (F) settings as well as the intensity of consumption in the inpatient (G) and outpatient (H) settings. P: preparation; I: intervention; A: assessment; *significant difference in intervention/assessment vs. preparation; ^#significant difference in assessment vs. intervention.</p

Regression analyses of ITS on the changes in patients’ costs.

<p>Changes in level and slope in patients’ costs on medications (ME), antibiotics (AN), and on the very-restricted (VR) antibiotics were analyzed for both inpatients and outpatients in the 65 general hospitals. Patients’ total costs during hospital stay (TO) were analyzed for inpatients. The parameters of β1 to β5, expressed as Mean (SE), were described in the Methods.</p><p>*<i>p</i> < 0.05;</p><p>** <i>p</i>< 0.01;</p><p>***<i>p</i> < 0.001.</p><p>Regression analyses of ITS on the changes in patients’ costs.</p