Idiosyncratic Drug-Induced Liver Injury: From Pathogenesis to Risk Reduction by I. A. Mazerkina

“…The identification of the allele combinations associated with an increased risk of iDILI seems promising for enhancing the predictive value of genetic studies and may be used in personalised medicine.…”
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Establishing an AI-based diagnostic framework for pulmonary nodules in computed tomography by Ruiting Jia, Baozhi Liu, Mohsin Ali

“…The diagnostic accuracy was 90.58%, with an overall positive predictive value of 89% and an overall negative predictive value of 86%. …”
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Evaluating the concordance between Vesical Imaging Reporting and Data System scores and bladder tumor histopathology by Hasan Gungor, Ahmet Camtosun, Ibrahim Topcu, Leyla Karaca

“…Sensitivity of the VI-RADS score was 100%; specificity was 23%; the negative predictive value was 100%; and the positive predictive value was 62%. …”
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A novel approach to overcome black box of AI for optical diagnosis in colonoscopy by Youmin Shin, Jung Ho Bae, Jung Kim, Jinwook Choi, Young-Gon Kim

“…Comparative evaluation showed that niceAI had accuracy comparable to that of deep learning models (area under the curve, 0.946; accuracy, 0.883; sensitivity, 0.888; specificity, 0.879; positive predictive value, 0.893; negative predictive value, 0.872). …”
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The usefulness of endoscopic ultrasonography in differentiation between benign and malignant gastric ulcer by Roganović Branka, Perišić Nenad, Roganović Ana

“…The total point score of ≥ 4 was the cut-off pointscore value which gave the best reliability parameters in the assessment of malignant ulcers: sensitivity of 70%, specificity of 95%, positive predictive value of 93.3%, negative predictive value of 76% and accuracy of 82.5%. …”
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Investigating the Sensitivity and Specificity of Fine Needle Aspiration Cytology for Diagnosing Malignant Liver Tumors by Paheli Maru, Vibha R Vyas, Varnika Rai, Shilpa Kapoor, Samanta Satarupa

“…The sensitivity, specificity, accuracy, positive predictive value and negative predictive value of FNAC in diagnosing malignant liver lesions in our center were 87.25%, 71.21% and 22.72% respectively. …”
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Four Node Sampling: Is It an Effective Alternative to Sentinel Lymph Node Biopsy in Low-resource Settings for Breast Cancer Management by Sreehari Pothina, Manisha Sharma, Puneet Takkar, Parameswar Reddy Gadikota

“…The performance of FNAS as an alternative to SLNB showed a sensitivity of 81%, specificity of 100%, positive predictive value of 100%, and negative predictive value (NPV) of 69%. …”
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ECG features improve multimodal deep learning prediction of incident T2DM in a Middle Eastern cohort by Farida Mohsen, Ali Safa, Zubair Shah

“…Furthermore, stratifying participants into Low-, Medium-, and High-risk categories revealed that ECG-DiaNet achieved a higher positive predictive value (PPV) in the high-risk group compared to CRF-only models. …”
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The effect of postoperative weight loss on difficult intubation in bariatric surgery patients: a prospective observational study by Bahar Uslu Bayhan, Kazım Ersin Altınsoy

“…ROC curve analysis was performed to evaluate the predictive value of preoperative parameters for difficult intubation. …”
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X-ray is not inferior to CT in terms of F1 score in the diagnosis of foreign body aspiration: a recall, precision and F1 score performance analysis based on bronchoscopically prove... by Fatma Sarac, Mehmet Yazici

“…Chest x-rays were found to exhibit 42 % sensitivity, 74 % specificity, a positive predictive value (PPV) of 61 %, a negative predictive value (NPV) of 51 %, accuracy of 66 %, precision: 0.63, recall: 0.82, and F1 score: 0.71. …”
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The accuracy of the Candida Score® in predicting the likelihood of fungal sepsis in newborns by Johanes Edy Siswanto, Milda, Dewi Patriani, Boromeus Abyasa Daniswara, Christophorus Adi S. Pamungkas

“…The revised Candida Score® showed sensitivity of 81.3%, specificity of 58.6%, positive predictive value (PPV) of 68.4%, negative predictive value (NPV) of 62.9%, and an area under the curve (AUC) of 0.743 (p = 0.001).Conclusion Incorporating outborn status and thrombocytopenia improved early identification of neonatal candidemia. …”
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Machine-learning of medical cannabis chemical profiles reveals analgesia beyond placebo expectations by Adi Hatav, Yelena Vysotski, Anna Shapira, Shiri Procaccia, David Meiri, Dvir Aran

“…We used a Random Forest classifier with nested cross-validation to assess the predictive value of demographics, clinical features, and approximately 200 chemical compounds. …”
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Increased serum uric acid to creatinine ratio is associated with metabolic dysfunction associated steatotic liver disease by Fang Wang, XuDong Zheng, Xiang Ni, Ying Li

“…Maybe SUA/SCr could be considered as a useful biomarker for MASLD in clinical work, although the predictive value is limited, and further validation and combined usage with other markers are necessary.…”
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Values of lymphocyte-related ratios in predicting the clinical outcome of acute ischemic stroke patients receiving intravenous thrombolysis based on different etiologies by Yongyu Li, Keyang Chen, Lu Wang, Linhu Zhao, Chunyan Lei, Yu Gu, Xiaoyan Zhu, Qionghua Deng

“…BackgroundWhile neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR) have been associated with acute ischemic stroke (AIS) outcomes, their differential predictive value across etiological subtypes (TOAST classification) in thrombolysis-treated patients remains underexplored.MethodsIn this retrospective cohort study, we analyzed 381 AIS patients receiving intravenous thrombolysis. …”
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Redefining Liver Fibrosis Risk Assessment in Indians with Type 2 Diabetes: New FIB-4 Score Cutoff for Optimizing Sequential Assessment with Transient Elastography by Rajat Deb, Soumik Goswami, Nilanjan Sengupta, Arjun Baidya, Vibhu R. Khare, Joydip Datta, Mousumi Das, Debes Ray

“…We found that a FIB-4 of 1.5 rules out CSLF with a sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and Diagnostic Accuracy (DA) of 82.9%, 79.9%, 55.7%, 93.8%, and 80.6%, respectively, compared with a FIB4 of 1.3 which has values of 91.5%, 67.3%, 46.1%, 96.2%, and 72.9%, respectively. …”
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Identification of the most common pathogenic bacteria in patients with suspected sepsis by multiplex PCR by Mohammad Reza Arabestani, Hossein Fazzeli, Bahram Nasr Esfahani

“…Results: The sensitivity and specificity for universal PCR and multiplex PCR in comparison with BC were 83.87% and 91.58%, and 74.19% and 91.58%, respectively. The positive predictive value (PPV) and the negative predictive value (NPV) for these two PCRs were 76.47% and 94.57%, and 74.19% and 91.58%, respectively. …”
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Labour Admission Test - A low cost alternative to predict foetal distress and neonatal outcomes by Chandini Sree Lalitha Chinta, Sarvamangala B

“…A statistical analysis comparing normal and abnormal (suspicious + pathological) AT showed high specificity 83.82% and high negative predictive value 92.95%. However, LAT was found to have low sensitivity 59.26% and low positive predictive value 36.36%. …”
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Epidemiological study of human brucellosis among febrile patients in Erbil-Kurdistan region, Iraq by Dhary Alewy Almashhadany, Zean Fetehallah Zefenkey, Mohammed Naji Ahmed Odhah

“…The sensitivity, specificity, positive predictive value, and negative predictive value of the Rose Bengal Test in comparison to the blood culture were 100%, 96.9%, 77.5 %, and 100% respectively. …”
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ASAS criteria for inflammatory back pain: diagnostic significance in patients with inflammatory bowel disease by E. N. Belousova, A. Kh. Odintsova, M. S. Protopopov, D. I. Abdulganieva

“…In our study, the sensitivity of the ASAS criteria for IBD was 76.9% and specificity – 67.2%, positive predictive value was 0.51, a negative predictive value – 0.87. …”
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Evaluating alternatives to the Widal test for typhoid fever diagnosis in developing countries: A targeted literature review by Bereket A. Tegene, Meron T. Eshetie

“…Results: The mean sensitivity, specificity, positive predictive value and negative predictive value of the Widal test in this study were 62.94 ± 17.83 (95% confidence interval [CI]: 49.23–76.64); 73.31 ± 18.75 (95% CI: 58.89–87.73); 58.85 ± 40.07 (95% CI: 16.80–100.90) and 75.96 ± 25.93 (95% CI: 46.08–100.45), respectively. …”
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