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25 papers · ranked by Valyu relevance

01
PPubMed24 Dec 2024
Beyond the null: Recognizing and reporting true negative findings
Manon K. Schweinfurth, Joachim G. Frommen
Title: Summary Science is based on ideas that might be true or false in describing reality. In order to discern between these two, scientists conduct studies that can reveal evidence for an idea, i.e., positive findings, or not, i.e., negative or null findings. The outcome of these studies can either be true, i.e.…
78relevance
02
AarXiv2022
Emphasis on the Minimization of False Negatives or False Positives in Binary Classification
Sanskriti Singh
—The minimization of specific cases in binary classification, such as false negatives or false positives, grows increasingly important as humans begin to implement more machine learning into current products. While there are a few methods to put a bias towards the reduction of specific cases, these methods aren't very…
77relevance
03
AarXiv19 Jun 2024
Large Language Models are Skeptics: False Negative Problem of Input-conflicting Hallucination
Jongyoon Song, Sangwon Yu, Sungroh Yoon
Input-conflicting Hallucination Authors: ['Jongyoon Song' 'Sangwon Yu' 'Sungroh Yoon'] In this paper, we identify a new category of bias that induces input-conflicting hallucinations, where large language models (LLMs) generate responses inconsistent with the content of the input context. This issue we have termed the…
76relevance
04
BbioRxiv23 Mar 2022
Recovering false negatives in CRISPR fitness screens with JLOE
Merve Dede, Traver Hart
It is widely accepted that pooled library CRISPR knockout screens offer greater sensitivity and specificity than prior technologies in detecting genes whose disruption leads to fitness defects, a critical step in identifying candidate cancer targets. However, the assumption that CRISPR screens are saturating has been…
75relevance
05
PPubMed28 Aug 2024
RT-qPCR Testing and Performance Metrics in the COVID-19 Era
Stephen A. Bustin, Eleni Gavriilaki
The COVID-19 pandemic highlighted the crucial role of diagnostic testing in managing infectious diseases, particularly through the use of reverse transcription-quantitative polymerase chain reaction (RT-qPCR) tests. RT-qPCR has been pivotal in detecting and quantifying viral RNA, enabling the identification and…
75relevance
06
CchemRxiv28 May 2025
Structure-Activity-Relationships can be directly extracted from high-throughput crystallographic evaluation of fragment elaborations in crude reaction mixtures
Authors not listed
Fragment hits serve as starting points for lead-like compound development. A common approach to advancing from fragments is to build structure-activity relationships (SARs) from close analogues. One strategy involves performing automated chemistry around fragment hits and evaluating resulting crude reaction mixtures…
73relevance
07
PPubMed29 Jun 2022
Accurate Interpretation of SARS-CoV-2 Antigen Detection by Immunochromatography
Wenxia Shao
SARS-CoV-2 is a serious infectious respiratory virus that can cause lung, heart, kidney, and liver damage and even cause death. Early diagnosis of SARS-CoV-2 infection is vital for epidemic prevention and control. At present, the gold standard of COVID-19 diagnosis is nucleic acid detection of SARS-CoV-2. However, the…
72relevance
08
PPubMed24 Sep 2024
Comment on Dijkstra et al. A False-Negative Newborn Screen for Tyrosinemia Type 1—Need for Re-Evaluation of Newborn Screening with Succinylacetone. <i> Int. J. Neonatal Screen. </i> 2023, <i> 9 </i> , 66
Marelle J. Bouva, Rose E. Maase, Ruurd M. van Elburg
The assessment of newborn screening (NBS) algorithms’ performance to ensure quality improvements is a continuous process: false-positive referrals can enable optimisations in the shorter term, but false-negative referrals are often only discovered many years after the screening has taken place. In their article ‘A…
72relevance
09
AarXiv22 Sep 2025
Medical priority fusion: achieving dual optimization of sensitivity and interpretability in nipt anomaly detection
Xin Ge, Zhibo Yao, Yao Du
Clinical machine learning faces a critical dilemma in high-stakes medical applications: algorithms achieving optimal diagnostic performance typically sacrifice the interpretability essential for physician decision-making, while interpretable methods compromise sensitivity in complex scenarios. This paradox becomes…
69relevance
10
AarXiv2022
Using artificial intelligence to detect chest X-rays with no significant findings in a primary health care setting in Oulu, Finland
Tommi Keski-Filppula, Marko Nikki, Marianne Haapea, Naglis Ramanauskas + 1 more
'Naglis Ramanauskas' 'Osmo Tervonen'] In this retrospective study, a commercially available artificial intelligence (AI) software was used to analyse 10 000 chest X-rays of Finnish primary health care patients. In studies with a mismatch between an AI normal report and the original radiologist report, a consensus read…
68relevance
11
BbioRxiv1 Mar 2022
Statistical notes on false positive and negative error rates in the evaluation of long-term carcinogenicity bioassays
Ludwig A. Hothorn
The appropriate interpretation of mortality-adjusted tumor incidences in long-term carcinogenicity bioassays depends substantially on the actual false positive and false negative error rates. These depend, among other things, on the type of analysis of multiple correlated tumor sites and the mode of dose-response…
68relevance
12
AarXiv2022
A deep learning algorithm for reducing false positives in screening mammography
Stefano Pedemonte, Trevor Tsue, Brent Mombourquette, Yen Nhi Truong Vu + 9 more
'Yen Nhi Truong Vu' 'Thomas P. Matthews' 'Rodrigo Morales Hoil' 'Meet Shah' 'Nikita Ghare' 'Naomi Zingman-Daniels' 'Susan Holley' 'Catherine M. Appleton' 'Jason Su' 'Richard L. Wahl'] Screening mammography improves breast cancer outcomes by enabling early detection and treatment. However, false positive callbacks for…
68relevance
13
BbioRxiv20 Jan 2022
Balancing sensitivity and specificity in preclinical research
Meggie Danziger, Anja Collazo, Ulrich Dirnagl, Ulf Toelch
The success of scientific discovery in preclinical research is based on the different roles of exploration and confirmation. Exploration involves identifying potential effects (high sensitivity), which are then tested more rigorously during confirmation (high specificity). Here, we examine different experimental…
67relevance
14
CchemRxiv18 Dec 2023
Deconvoluting Low Yield from Weak Potency in Direct-to-Biology Workflows with Machine Learning
William McCorkindale, Mihajlo Filep, Nir London, Alpha A. Lee + 1 more
High throughput and rapid biological evaluation of small molecules is an essential factor in drug discovery and development. Direct-to-Biology (D2B), whereby compound purification is foregone, has emerged as a viable technique in time efficient screening, specifically for PROTAC design and biological evaluation.…
66relevance
15
CchemRxiv3 Oct 2022
LFQ-based peptide and protein intensity downstream analysis
Mingze Bai, Jingwen Deng, Chengxin Dai, Julianus Pfeuffer + 1 more
Testing for significant differences in quantities on protein level is a common goal of many LFQ-based mass spectrometry proteomics experiments. Starting from a table of protein and/or peptide quantities from a fixed proteomics quantification software, there exists a multitude of tools and R packages to perform the…
65relevance
16
PPubMed28 Dec 2022
Correcting Diagnostic Test Sensitivity and Specificity for Patient Misclassifications Resulting from Use of an Imperfect Reference Standard
Paul F. Sherwin, Michael Nagler
Investigational diagnostic tests are validated by using a reference standard (RS). If the RS is imperfect (i.e., it has sensitivity [Se] and/or specificity [Sp] < 1), incorrect values for the investigational test’s Se and Sp may result because of patient misclassification by the RS. Formulas were derived to correct a…
65relevance
17
BbioRxiv25 Nov 2023
An Efficient Computational Method to Create Positive NIPT Samples with Autosomal Trisomy
Tinh H. Nguyen, Huynh V. Nguyen, Minh D. Pham, Vinh S. Le
Noninvasive prenatal test (NIPT) has been widely used for screening trisomy on chromosomes 13 (T13), 18 (T18), and 21 (T21). However, the false negative rate of NIPT algorithms has not been thoroughly evaluated due to the lack of positive samples. In this study, we present an efficient computational approach to…
64relevance
18
BbioRxiv16 Feb 2022
Robust statistical evaluation of tumor incidences in long-term rodent carcinogenicity studies: the reformulated poly-k trend test
Ludwig A. Hothorn
Mortality-adjusted tumor rates in long-term carcinogenicity rodent bioassays are commonly evaluated by means of the poly-k=3 Armitage trend test. However, this assumes exactly a linear dose-response curve and the Weibull parameter of k=3 for all tumor sites. These unrealistic assumptions can be circumvented by multiple…
64relevance
19
AarXiv2022
Some reflections on the test-negative design
Ronald Meester, J Bonte
The test-negative design was developed as a method to estimate influenza vaccine effectiveness, but has more recently also been used in the context of COVID-19 vaccines [1, 3, 5, 6, 7, 8, 9, 10, 11]. In this contribution, we discuss the vaccine effectivity as defined through a test-negative design study. Clearly, in…
63relevance
20
BbioRxiv13 Apr 2024
A Lipidomics-Based Method to Eliminate Negative Urine Culture in General Population
Linda K Nartey, Abanoub Mikhael, Helena Pětrošová, Victor Yuen + 4 more
Urinary tract infections (UTIs) pose a significant challenge to human health. Accurate and timely detection remains pivotal for effective intervention. Current urine culture techniques, while essential, often encounter challenges where urinalysis yields positive results, but subsequent culture testing produces a…
62relevance
21
CchemRxiv5 Dec 2023
Machine learning assisted hit prioritization for high throughput screening in drug discovery
Davide Boldini, Lukas Friedrich, Daniel Kuhn, Stephan Sieber
Efficient prioritization of bioactive compounds from high throughput screening campaigns is a fundamental challenge for accelerating drug development efforts. In this study, we present the first data-driven approach to simultaneously detect assay interferents and prioritize true bioactive compounds. By analyzing the…
61relevance
22
CchemRxiv4 Jan 2023
Diagnosis of Viral Infections: A Review of the Current Assays and the Prediction of the Future
Sanghyuk Ko
Different types of diagnostics methods were introduced to the public due to the recent global pandemic. From the real-time reverse transcript polymerase chain reaction (RT-qPCR) to antigen lateral flow assay (LFA), these tests allow relatively accurate and rapid diagnosis of the infection with SARS-CoV-2 virus. Because…
59relevance
23
CchemRxiv12 Dec 2023
Data Valuation: A novel approach for analyzing high throughput screen data using machine learning
Joshua Hesse, Davide Boldini, Stephan Sieber
In the rapidly evolving field of drug discovery, High Throughput Screening (HTS) is a pivotal technique for identifying promising compounds. Despite its wide usage, the primary challenge remains in efficiently sifting through vast chemical libraries to discern true bioactive compounds from false positives. This study…
58relevance
24
AarXiv7 May 2026
CXR-ContraBench: Benchmarking Negated-Option Attraction in Medical VLMs
Zhengru Fang, Yanan Ma, Yu Guo, Senkang Hu + 4 more
When a chest X-ray shows consolidation but the question asks which finding is present, a medical vision-language model may answer "No consolidation." This is more than an incorrect choice: it is a polarity reversal that emits a clinical statement contradicting the image. We study this failure as negated-option…
53relevance
25
PPubMed24 Oct 2025
Factors associated with false positive results in serological testing for syphilis using EIA among children
Jiaqi Liu, Qianqian Chen, Guangchao Zhao, Xuzhou Fan + 1 more
Objectives The issue of biological false positives in syphilis diagnosis is gaining attention. However, limited focus exists on false positives in syphilis tests among younger populations. This study investigates the epidemiological characteristics and influencing factors of false positive serological test results for…
53relevance

Results for false negative

Beyond the null: Recognizing and reporting true negative findings

Emphasis on the Minimization of False Negatives or False Positives in Binary Classification

Large Language Models are Skeptics: False Negative Problem of Input-conflicting Hallucination

Recovering false negatives in CRISPR fitness screens with JLOE

RT-qPCR Testing and Performance Metrics in the COVID-19 Era

Structure-Activity-Relationships can be directly extracted from high-throughput crystallographic evaluation of fragment elaborations in crude reaction mixtures

Accurate Interpretation of SARS-CoV-2 Antigen Detection by Immunochromatography

Comment on Dijkstra et al. A False-Negative Newborn Screen for Tyrosinemia Type 1—Need for Re-Evaluation of Newborn Screening with Succinylacetone. <i> Int. J. Neonatal Screen. </i> 2023, <i> 9 </i> , 66

Medical priority fusion: achieving dual optimization of sensitivity and interpretability in nipt anomaly detection

Using artificial intelligence to detect chest X-rays with no significant findings in a primary health care setting in Oulu, Finland

Statistical notes on false positive and negative error rates in the evaluation of long-term carcinogenicity bioassays

A deep learning algorithm for reducing false positives in screening mammography

Balancing sensitivity and specificity in preclinical research

Deconvoluting Low Yield from Weak Potency in Direct-to-Biology Workflows with Machine Learning

LFQ-based peptide and protein intensity downstream analysis

Correcting Diagnostic Test Sensitivity and Specificity for Patient Misclassifications Resulting from Use of an Imperfect Reference Standard

An Efficient Computational Method to Create Positive NIPT Samples with Autosomal Trisomy

Robust statistical evaluation of tumor incidences in long-term rodent carcinogenicity studies: the reformulated poly-k trend test

Some reflections on the test-negative design

A Lipidomics-Based Method to Eliminate Negative Urine Culture in General Population

Machine learning assisted hit prioritization for high throughput screening in drug discovery

Diagnosis of Viral Infections: A Review of the Current Assays and the Prediction of the Future

Data Valuation: A novel approach for analyzing high throughput screen data using machine learning

CXR-ContraBench: Benchmarking Negated-Option Attraction in Medical VLMs

Factors associated with false positive results in serological testing for syphilis using EIA among children

Beyond the null: Recognizing and reporting true negative findings

Emphasis on the Minimization of False Negatives or False Positives in Binary Classification

Large Language Models are Skeptics: False Negative Problem of Input-conflicting Hallucination

Recovering false negatives in CRISPR fitness screens with JLOE

RT-qPCR Testing and Performance Metrics in the COVID-19 Era

Structure-Activity-Relationships can be directly extracted from high-throughput crystallographic evaluation of fragment elaborations in crude reaction mixtures

Accurate Interpretation of SARS-CoV-2 Antigen Detection by Immunochromatography

Comment on Dijkstra et al. A False-Negative Newborn Screen for Tyrosinemia Type 1—Need for Re-Evaluation of Newborn Screening with Succinylacetone. <i> Int. J. Neonatal Screen. </i> 2023, <i> 9 </i> , 66

Medical priority fusion: achieving dual optimization of sensitivity and interpretability in nipt anomaly detection

Using artificial intelligence to detect chest X-rays with no significant findings in a primary health care setting in Oulu, Finland

Statistical notes on false positive and negative error rates in the evaluation of long-term carcinogenicity bioassays

A deep learning algorithm for reducing false positives in screening mammography

Balancing sensitivity and specificity in preclinical research

Deconvoluting Low Yield from Weak Potency in Direct-to-Biology Workflows with Machine Learning

LFQ-based peptide and protein intensity downstream analysis

Correcting Diagnostic Test Sensitivity and Specificity for Patient Misclassifications Resulting from Use of an Imperfect Reference Standard

An Efficient Computational Method to Create Positive NIPT Samples with Autosomal Trisomy

Robust statistical evaluation of tumor incidences in long-term rodent carcinogenicity studies: the reformulated poly-k trend test

Some reflections on the test-negative design

A Lipidomics-Based Method to Eliminate Negative Urine Culture in General Population

Machine learning assisted hit prioritization for high throughput screening in drug discovery

Diagnosis of Viral Infections: A Review of the Current Assays and the Prediction of the Future

Data Valuation: A novel approach for analyzing high throughput screen data using machine learning

CXR-ContraBench: Benchmarking Negated-Option Attraction in Medical VLMs

Factors associated with false positive results in serological testing for syphilis using EIA among children